RQ4_STEM_integration.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os \n",
    "import sys \n",
    "import shutil\n",
    "import json\n",
    "import glob"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "oss.krtirtho.spotube_31\n",
      "org.asafonov.monly_47\n",
      "lying.fengfeng.foodrecords_1\n",
      "galaxy_store\n",
      "familyfinance\n",
      "org.tasks_130909\n",
      "com.ichi2.anki_21803300\n",
      "luci.sixsixsix.powerampache2.fdroid_59\n",
      "moe.dic1911.urlsanitizer_30\n",
      "com.nextcloud.talk2_190000190\n",
      "com.moimob.drinkable_15000\n",
      "com.money.manager.ex_1032\n",
      "aeroflot\n",
      "Missing: 0\n",
      "Exist: 13\n"
     ]
    }
   ],
   "source": [
    "missing = 0\n",
    "exist = 0\n",
    "\n",
    "for output_dir in os.listdir('./stem_output_context_2'):\n",
    "    output_dir = os.path.join('./stem_output_context_2', output_dir)\n",
    "    if os.path.isdir(output_dir):\n",
    "        if not os.path.exists(os.path.join(output_dir, 'summary.json')):\n",
    "            print('Missing index.html in {}'.format(output_dir))\n",
    "            missing += 1\n",
    "        else:\n",
    "            with open(os.path.join(output_dir, 'summary.json'), 'r') as f:\n",
    "                summary = json.load(f)\n",
    "\n",
    "            if summary['time_spent'] < 1600:\n",
    "                print(f'Time spent less than 1600 seconds in {output_dir} (time spent: {summary[\"time_spent\"]})')\n",
    "                missing += 1\n",
    "            else:\n",
    "                print(os.path.basename(output_dir))\n",
    "                exist += 1\n",
    "\n",
    "print('Missing: {}'.format(missing))\n",
    "print('Exist: {}'.format(exist))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [],
   "source": [
    "import xml.etree.ElementTree as ET\n",
    "import glob\n",
    "\n",
    "def extract_activity_names(manifest_file):\n",
    "    # Parse the XML file\n",
    "    tree = ET.parse(manifest_file)\n",
    "    root = tree.getroot()\n",
    "\n",
    "    # Namespace dictionary to handle Android namespace\n",
    "    namespaces = {'android': 'http://schemas.android.com/apk/res/android'}\n",
    "\n",
    "    # Find all activity elements and extract their android:name attributes\n",
    "    activities = root.findall(\".//activity\", namespaces)\n",
    "    activity_names = [activity.get('{http://schemas.android.com/apk/res/android}name') for activity in activities]\n",
    "\n",
    "    return activity_names\n",
    "\n",
    "appname2activities = {}\n",
    "\n",
    "for manifest_file in glob.glob('rq2_targets/*/AndroidManifest.xml'):\n",
    "    app_name = os.path.basename(os.path.dirname(manifest_file))\n",
    "\n",
    "    appname2activities[app_name] = {\n",
    "        'raw': [],\n",
    "        'last': []\n",
    "    }\n",
    "\n",
    "    # Extract activity names\n",
    "    for name in extract_activity_names(manifest_file):\n",
    "        appname2activities[app_name]['raw'].append(name)\n",
    "        appname2activities[app_name]['last'].append(name.split('.')[-1])\n",
    "        \n",
    "\n",
    "# with open('activities_map.json', 'w') as f:\n",
    "#     json.dump(appname2activities, f, indent=2)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open('activities_map.json') as f:\n",
    "    activities_map = json.load(f)\n",
    "\n",
    "def is_valid_activity(app_name, activity_name):\n",
    "    valid_activities = activities_map[app_name]['last']\n",
    "\n",
    "    activity_name_cleaned = activity_name.split('.')[-1]\n",
    "    if activity_name_cleaned in valid_activities:\n",
    "        return True\n",
    "    else:\n",
    "        return False\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "oss.krtirtho.spotube_31\n",
      "reached_activities (DroidFiller) {'HomeDashboardActivity', 'Settings$WifiSettingsActivity', 'Settings$UsbDetailsActivity', 'RequestIgnoreBatteryOptimizations', 'LauncherActivity', 'AudioServiceActivity', 'CustomControlsActivity', 'InternalGoogleAppActivityEntrypoint', 'BluetoothScanDialog'} (9)\n",
      "reached_activities (Context) {'FeedbackAlohaActivity', 'RequestIgnoreBatteryOptimizations', 'LauncherActivity', 'AudioServiceActivity', 'BatteryActivity', 'CustomControlsActivity', 'InternalGoogleAppActivityEntrypoint', 'CustomTabActivity'} (8)\n",
      "internal_activities (DroidFiller) ['AudioServiceActivity'] (1)\n",
      "internal_activities (Context) ['AudioServiceActivity'] (1)\n",
      "\n",
      "---\n",
      "\n",
      "org.asafonov.monly_47\n",
      "reached_activities (DroidFiller) {'LauncherActivity', 'MainActivity'} (2)\n",
      "reached_activities (Context) {'LauncherActivity', 'MainActivity'} (2)\n",
      "internal_activities (DroidFiller) ['MainActivity'] (1)\n",
      "internal_activities (Context) ['MainActivity'] (1)\n",
      "\n",
      "---\n",
      "\n",
      "lying.fengfeng.foodrecords_1\n",
      "reached_activities (DroidFiller) {'LauncherActivity', 'MainActivity', 'AppErrorDialogActivity'} (3)\n",
      "reached_activities (Context) {'LauncherActivity', 'MainActivity'} (2)\n",
      "internal_activities (DroidFiller) ['MainActivity'] (1)\n",
      "internal_activities (Context) ['MainActivity'] (1)\n",
      "\n",
      "---\n",
      "\n",
      "familyfinance\n",
      "reached_activities (DroidFiller) {'IncomeOperationActivity', 'ExpenseArticleEditActivity', 'IncomeArticleEditActivity', 'TransferOperationEditActivity', 'DashboardActivity', 'SmsPatternEditActivity', 'InstalledAppDetails', 'IncomeOperationEditActivity', 'CurrencyEditActivity', 'TemplateEditActivity', 'IconicsActivity', 'TemplateActivity', 'IncomeArticleActivity', 'TransferOperationActivity', 'ExchangeRateActivity', 'PersonActivity', 'AccountActivity', 'FlowOfFundsOperationActivity', 'LauncherActivity', 'PersonEditActivity', 'AccountEditActivity', 'BackupActivity', 'SettingsActivity', 'ExpenseOperationEditActivity', 'ExpenseArticleActivity', 'ComposeActivityGmailExternal', 'ChartActivity', 'AllArticleActivity', 'ExchangeRateEditActivity', 'ChooserActivity', 'SmsPatternActivity'} (31)\n",
      "reached_activities (Context) {'ExpenseArticleEditActivity', 'ExpenseOperationActivity', 'TransferOperationEditActivity', 'IncomeArticleEditActivity', 'DashboardActivity', 'SmsPatternEditActivity', 'InstalledAppDetails', 'IncomeOperationEditActivity', 'IconicsActivity', 'TemplateActivity', 'IncomeArticleActivity', 'ExchangeRateActivity', 'PersonActivity', 'AccountActivity', 'FlowOfFundsOperationActivity', 'LauncherActivity', 'AccountEditActivity', 'ExpenseOperationEditActivity', 'ExpenseArticleActivity', 'ChartActivity', 'AllArticleActivity', 'SmsPatternActivity'} (22)\n",
      "internal_activities (DroidFiller) ['IncomeOperationActivity', 'ExpenseArticleEditActivity', 'IncomeArticleEditActivity', 'TransferOperationEditActivity', 'DashboardActivity', 'SmsPatternEditActivity', 'IncomeOperationEditActivity', 'CurrencyEditActivity', 'TemplateEditActivity', 'IconicsActivity', 'TemplateActivity', 'IncomeArticleActivity', 'TransferOperationActivity', 'ExchangeRateActivity', 'PersonActivity', 'AccountActivity', 'FlowOfFundsOperationActivity', 'PersonEditActivity', 'AccountEditActivity', 'BackupActivity', 'SettingsActivity', 'ExpenseOperationEditActivity', 'ExpenseArticleActivity', 'ChartActivity', 'AllArticleActivity', 'ExchangeRateEditActivity', 'SmsPatternActivity'] (27)\n",
      "internal_activities (Context) ['ExpenseArticleEditActivity', 'ExpenseOperationActivity', 'TransferOperationEditActivity', 'IncomeArticleEditActivity', 'DashboardActivity', 'SmsPatternEditActivity', 'IncomeOperationEditActivity', 'IconicsActivity', 'TemplateActivity', 'IncomeArticleActivity', 'ExchangeRateActivity', 'PersonActivity', 'AccountActivity', 'FlowOfFundsOperationActivity', 'AccountEditActivity', 'ExpenseOperationEditActivity', 'ExpenseArticleActivity', 'ChartActivity', 'AllArticleActivity', 'SmsPatternActivity'] (20)\n",
      "\n",
      "---\n",
      "\n",
      "org.tasks_130909\n",
      "reached_activities (DroidFiller) {'SortSettingsActivity', 'Camera', 'GoogleTTSActivity', 'TaskListActivity', 'CustomRecurrenceActivity', 'LocationPickerActivity', 'LauncherActivity', 'TagPickerActivity'} (8)\n",
      "reached_activities (Context) {'SortSettingsActivity', 'ConversationComposer', 'MapsActivity', 'GoogleTTSActivity', 'Camera', 'TaskListActivity', 'LocationPickerActivity', 'LauncherActivity', 'TagPickerActivity', 'PlaceSettingsActivity'} (10)\n",
      "internal_activities (DroidFiller) ['SortSettingsActivity', 'CustomRecurrenceActivity', 'LocationPickerActivity', 'TagPickerActivity'] (4)\n",
      "internal_activities (Context) ['SortSettingsActivity', 'LocationPickerActivity', 'TagPickerActivity', 'PlaceSettingsActivity'] (4)\n",
      "\n",
      "---\n",
      "\n",
      "com.ichi2.anki_21803300\n",
      "reached_activities (DroidFiller) {'ResolverActivity', 'MultimediaEditFieldActivity', 'NoteEditor', 'MainActivity', 'CardBrowser', 'CardViewerActivity', 'GalleryExternalActivity', 'CameraSettingActivity', 'ShareActivity', 'Preferences', 'SingleFragmentActivity', 'IntroductionActivity', 'CardTemplateEditor', 'DeckPicker', 'PickerActivity', 'Camera', 'SharedDecksActivity', 'LauncherActivity', 'MyAccount', 'CustomTabActivity', 'Reviewer', 'ComposeActivityGmailExternal', 'AnkiDroidCrashReportDialog', 'SwipeShutterButtonToActivity', 'WatermarkActivity', 'SBrowserMainActivity', 'ManageNotetypes', 'ChooserActivity', 'ImageOcclusionActivity', 'PickActivity'} (30)\n",
      "reached_activities (Context) {'ResolverActivity', 'SingleFragmentActivity', 'SharedDecksActivity', 'AnkiDroidCrashReportDialog', 'CardTemplateEditor', 'DeckPicker', 'LauncherActivity', 'Preferences', 'NoteEditor', 'ImageOcclusionActivity', 'ChooserActivity', 'CardBrowser', 'IntroductionActivity', 'LoginActivity', 'CustomTabActivity', 'PickActivity'} (16)\n",
      "internal_activities (DroidFiller) ['MultimediaEditFieldActivity', 'NoteEditor', 'CardBrowser', 'CardViewerActivity', 'Preferences', 'SingleFragmentActivity', 'IntroductionActivity', 'CardTemplateEditor', 'DeckPicker', 'SharedDecksActivity', 'MyAccount', 'Reviewer', 'AnkiDroidCrashReportDialog', 'ManageNotetypes', 'ImageOcclusionActivity'] (15)\n",
      "internal_activities (Context) ['SingleFragmentActivity', 'SharedDecksActivity', 'AnkiDroidCrashReportDialog', 'CardTemplateEditor', 'DeckPicker', 'Preferences', 'NoteEditor', 'ImageOcclusionActivity', 'CardBrowser', 'IntroductionActivity', 'LoginActivity'] (11)\n",
      "\n",
      "---\n",
      "\n",
      "luci.sixsixsix.powerampache2.fdroid_59\n",
      "reached_activities (DroidFiller) {'ComposeActivityGmailExternal', 'ShareActivity', 'LauncherActivity', 'InstallConfirmActivity', 'MainActivity', 'ChooserActivity'} (6)\n",
      "reached_activities (Context) {'ComposeActivityGmailExternal', 'ShareActivity', 'HelpIntroActivity', 'LauncherActivity', 'MainActivity', 'ChooserActivity'} (6)\n",
      "internal_activities (DroidFiller) ['MainActivity'] (1)\n",
      "internal_activities (Context) ['MainActivity'] (1)\n",
      "\n",
      "---\n",
      "\n",
      "moe.dic1911.urlsanitizer_30\n",
      "reached_activities (DroidFiller) {'LauncherActivity', 'MainActivity', 'PrivacyRedirectActivity', 'EntryListActivity'} (4)\n",
      "reached_activities (Context) {'LauncherActivity', 'MainActivity', 'PrivacyRedirectActivity', 'EntryListActivity'} (4)\n",
      "internal_activities (DroidFiller) ['MainActivity', 'PrivacyRedirectActivity', 'EntryListActivity'] (3)\n",
      "internal_activities (Context) ['MainActivity', 'PrivacyRedirectActivity', 'EntryListActivity'] (3)\n",
      "\n",
      "---\n",
      "\n",
      "com.nextcloud.talk2_190000190\n",
      "reached_activities (DroidFiller) {'LauncherActivity', 'SBrowserMainActivity', 'ServerSelectionActivity', 'WebViewLoginActivity'} (4)\n",
      "reached_activities (Context) {'LauncherActivity', 'SBrowserMainActivity', 'ServerSelectionActivity'} (3)\n",
      "internal_activities (DroidFiller) ['ServerSelectionActivity', 'WebViewLoginActivity'] (2)\n",
      "internal_activities (Context) ['ServerSelectionActivity'] (1)\n",
      "\n",
      "---\n",
      "\n",
      "com.moimob.drinkable_15000\n",
      "reached_activities (DroidFiller) {'LauncherActivity', 'MainActivity'} (2)\n",
      "reached_activities (Context) {'LauncherActivity', 'MainActivity'} (2)\n",
      "internal_activities (DroidFiller) ['MainActivity'] (1)\n",
      "internal_activities (Context) ['MainActivity'] (1)\n",
      "\n",
      "---\n",
      "\n",
      "com.money.manager.ex_1032\n",
      "reached_activities (DroidFiller) {'PayeeActivity', 'SyncPreferencesActivity', 'SearchActivity', 'SBrowserMainActivity', 'LauncherActivity', 'PasswordActivity', 'InvestmentSettingsActivity', 'AccountEditActivity', 'AboutActivity', 'SettingsActivity', 'MainActivity', 'TutorialActivity', 'SelectDatabaseActivity', 'CategoryListActivity', 'GeneralSettingsActivity', 'PickActivity'} (16)\n",
      "reached_activities (Context) {'ConversationsListActivity', 'MainActivity', 'SelectDatabaseActivity', 'GeneralSettingsActivity', 'PasswordActivity', 'CalculatorActivity', 'AboutActivity', 'BehaviourSettingsActivity', 'PayeeActivity', 'LauncherActivity', 'AccountEditActivity', 'SettingsActivity', 'RecurringTransactionEditActivity', 'SearchActivity', 'SBrowserMainActivity', 'TutorialActivity', 'ChooserActivity', 'BudgetsActivity', 'CategoryListActivity', 'PickActivity'} (20)\n",
      "internal_activities (DroidFiller) ['PayeeActivity', 'SyncPreferencesActivity', 'SearchActivity', 'PasswordActivity', 'InvestmentSettingsActivity', 'AccountEditActivity', 'AboutActivity', 'SettingsActivity', 'MainActivity', 'TutorialActivity', 'SelectDatabaseActivity', 'CategoryListActivity', 'GeneralSettingsActivity'] (13)\n",
      "internal_activities (Context) ['MainActivity', 'SelectDatabaseActivity', 'GeneralSettingsActivity', 'PasswordActivity', 'CalculatorActivity', 'AboutActivity', 'BehaviourSettingsActivity', 'PayeeActivity', 'AccountEditActivity', 'SettingsActivity', 'RecurringTransactionEditActivity', 'SearchActivity', 'TutorialActivity', 'BudgetsActivity', 'CategoryListActivity'] (15)\n",
      "\n",
      "---\n",
      "\n",
      "aeroflot\n",
      "reached_activities (DroidFiller) {'BookingDetailsActivity', 'GiftCertificateActivity', 'CitySearchActivity', 'LauncherActivity', 'WebViewActivity', 'BusinessPassActivity', 'CorporateLoyaltyProgramActivity', 'AeroflotBonusActivity', 'MainActivity', 'TravelGuideActivity', 'InformationActivity'} (11)\n",
      "reached_activities (Context) {'BookingDetailsActivity', 'GiftCertificateActivity', 'CitySearchActivity', 'LauncherActivity', 'WebViewActivity', 'CorporateLoyaltyProgramActivity', 'AeroflotBonusActivity', 'MainActivity', 'TravelGuideActivity'} (9)\n",
      "internal_activities (DroidFiller) ['BookingDetailsActivity', 'GiftCertificateActivity', 'CitySearchActivity', 'WebViewActivity', 'BusinessPassActivity', 'CorporateLoyaltyProgramActivity', 'AeroflotBonusActivity', 'MainActivity', 'TravelGuideActivity', 'InformationActivity'] (10)\n",
      "internal_activities (Context) ['BookingDetailsActivity', 'GiftCertificateActivity', 'CitySearchActivity', 'WebViewActivity', 'CorporateLoyaltyProgramActivity', 'AeroflotBonusActivity', 'MainActivity', 'TravelGuideActivity'] (8)\n",
      "\n",
      "---\n",
      "\n",
      "Missing: []\n"
     ]
    }
   ],
   "source": [
    "missing = []\n",
    "\n",
    "results = []\n",
    "full_results = []\n",
    "time_results = []\n",
    "\n",
    "INCLUDE_MULTI_RUN_RESULTS = True\n",
    "\n",
    "for output_dir in glob.glob('./stem_output_droidfiller/*'):\n",
    "    output_dir_2 = output_dir.replace('stem_output_droidfiller', 'stem_output_droidfiller_2')\n",
    "    output_dir_3 = output_dir.replace('stem_output_droidfiller', 'stem_output_droidfiller_3')\n",
    "\n",
    "    if os.path.isdir(output_dir):\n",
    "        app_id = os.path.basename(output_dir)\n",
    "        if not os.path.exists(os.path.join(output_dir, 'summary.json')):\n",
    "            print('Missing index.html in {}'.format(output_dir))\n",
    "            missing.append(app_id)\n",
    "        elif INCLUDE_MULTI_RUN_RESULTS and not os.path.exists(os.path.join(output_dir_2, 'summary.json')):\n",
    "            print('Missing index.html in {}'.format(output_dir_2))\n",
    "            missing.append(app_id)\n",
    "        elif INCLUDE_MULTI_RUN_RESULTS and not os.path.exists(os.path.join(output_dir_3, 'summary.json')):\n",
    "            print('Missing index.html in {}'.format(output_dir_3))\n",
    "            missing.append(app_id)\n",
    "        else:\n",
    "            summary = []\n",
    "            \n",
    "            with open(os.path.join(output_dir, 'summary.json'), 'r') as f:\n",
    "                summary = json.load(f)\n",
    "\n",
    "            with open(os.path.join(output_dir, 'utg.json'), 'r') as f:\n",
    "                utg = json.load(f)\n",
    "\n",
    "            if INCLUDE_MULTI_RUN_RESULTS:\n",
    "                with open(os.path.join(output_dir_2, 'summary.json'), 'r') as f:\n",
    "                    summary_2 = json.load(f)\n",
    "\n",
    "                with open(os.path.join(output_dir_2, 'utg.json'), 'r') as f:\n",
    "                    utg_2 = json.load(f)\n",
    "\n",
    "                state2activity_2 = {}\n",
    "                for node in utg_2['nodes']:\n",
    "                    if 'activity' not in node:\n",
    "                        continue\n",
    "                    state2activity_2[node['id']] = node['activity'].split('.')[-1]\n",
    "\n",
    "\n",
    "                with open(os.path.join(output_dir_3, 'summary.json'), 'r') as f:\n",
    "                    summary_3 = json.load(f)\n",
    "\n",
    "                with open(os.path.join(output_dir_3, 'utg.json'), 'r') as f:\n",
    "                    utg_3 = json.load(f)\n",
    "\n",
    "                state2activity_3 = {}\n",
    "                for node in utg_3['nodes']:\n",
    "                    if 'activity' not in node:\n",
    "                        continue\n",
    "                    state2activity_3[node['id']] = node['activity'].split('.')[-1]\n",
    "\n",
    "            state2activity = {}\n",
    "            for node in utg['nodes']:\n",
    "                if 'activity' not in node:\n",
    "                    continue\n",
    "                state2activity[node['id']] = node['activity'].split('.')[-1]\n",
    "\n",
    "            if summary['time_spent'] < 1000:\n",
    "                print(f'Time spent less than 1600 seconds in {output_dir} (time spent: {summary[\"time_spent\"]})')\n",
    "                missing.append(app_id)\n",
    "            elif INCLUDE_MULTI_RUN_RESULTS and summary_2['time_spent'] < 1000:\n",
    "                print(f'Time spent less than 1600 seconds in {output_dir_2} (time spent: {summary_2[\"time_spent\"]})')\n",
    "                missing.append(app_id)\n",
    "            elif INCLUDE_MULTI_RUN_RESULTS and summary_3['time_spent'] < 1000:\n",
    "                print(f'Time spent less than 1600 seconds in {output_dir_3} (time spent: {summary_3[\"time_spent\"]})')\n",
    "                missing.append(app_id)\n",
    "            else:\n",
    "                num_set_text = [0, 0, 0]\n",
    "                reached_activities = [set(), set(), set()]\n",
    "                reached_activities_context = [set(), set(), set()]\n",
    "                covered_states = [set(), set(), set()]\n",
    "\n",
    "                with open(f'./stem_output_context/{app_id}/summary.json') as f:\n",
    "                    summary_context = json.load(f)\n",
    "\n",
    "                with open(f'./stem_output_context/{app_id}/utg.json') as f:\n",
    "                    utg_context = json.load(f)\n",
    "\n",
    "                state2activity_context = {}\n",
    "                for node in utg_context['nodes']:\n",
    "                    if 'activity' not in node:\n",
    "                        continue\n",
    "                    state2activity_context[node['id']] = node['activity'].split('.')[-1]\n",
    "\n",
    "                min_event_count = min(summary['num_input_events'], summary_context['num_input_events'])\n",
    "\n",
    "                if INCLUDE_MULTI_RUN_RESULTS:\n",
    "                    with open(f'./stem_output_context_2/{app_id}/summary.json') as f:\n",
    "                        summary_context_2 = json.load(f)\n",
    "\n",
    "                    with open(f'./stem_output_context_2/{app_id}/utg.json') as f:\n",
    "                        utg_context_2 = json.load(f)\n",
    "\n",
    "                    state2activity_context_2 = {}\n",
    "                    for node in utg_context_2['nodes']:\n",
    "                        if 'activity' not in node:\n",
    "                            continue\n",
    "                        state2activity_context_2[node['id']] = node['activity'].split('.')[-1]\n",
    "\n",
    "                    with open(f'./stem_output_context_3/{app_id}/summary.json') as f:\n",
    "                        summary_context_3 = json.load(f)\n",
    "\n",
    "                    with open(f'./stem_output_context_3/{app_id}/utg.json') as f:\n",
    "                        utg_context_3 = json.load(f)\n",
    "\n",
    "                    state2activity_context_3 = {}\n",
    "                    for node in utg_context_3['nodes']:\n",
    "                        if 'activity' not in node:\n",
    "                            continue\n",
    "                        state2activity_context_3[node['id']] = node['activity'].split('.')[-1]\n",
    "\n",
    "                    min_event_count = min(summary['num_input_events'], summary_context['num_input_events'], summary_2['num_input_events'], summary_context_2['num_input_events'], summary_3['num_input_events'], summary_context_3['num_input_events'])\n",
    "\n",
    "                with open(os.path.join(output_dir, 'app_info.json')) as f:\n",
    "                    package_name = json.load(f)['app_package']\n",
    "\n",
    "                with open(os.path.join(output_dir, 'eventlist.json')) as f:\n",
    "                    eventlist = json.load(f)\n",
    "                    for i, event in enumerate(eventlist):\n",
    "                        if i >= min_event_count:\n",
    "                            break\n",
    "\n",
    "                        if event['event']['event_type'] == 'set_text':\n",
    "                            num_set_text[0] += 1\n",
    "\n",
    "                        from_state = event['from']\n",
    "                        to_state = event['to']\n",
    "\n",
    "                        if from_state in state2activity:\n",
    "                            reached_activities[0].add(state2activity[from_state])\n",
    "                            if is_valid_activity(app_id, state2activity[from_state]):\n",
    "                                covered_states[0].add(from_state)\n",
    "\n",
    "                        if to_state in state2activity:\n",
    "                            reached_activities[0].add(state2activity[to_state])\n",
    "                            if is_valid_activity(app_id, state2activity[to_state]):\n",
    "                                covered_states[0].add(to_state)\n",
    "\n",
    "                        time_results.append({\n",
    "                            'technique': 'DroidFiller',\n",
    "                            'app_id': app_id,\n",
    "                            'event_no': i+1,\n",
    "                            'num_covered_activities': len([a for a in reached_activities[0] if is_valid_activity(app_id, a)]),\n",
    "                        })\n",
    "\n",
    "                if INCLUDE_MULTI_RUN_RESULTS:\n",
    "                    with open(os.path.join(output_dir_2, 'app_info.json')) as f:\n",
    "                        package_name = json.load(f)['app_package']\n",
    "\n",
    "                    with open(os.path.join(output_dir_2, 'eventlist.json')) as f:\n",
    "                        eventlist = json.load(f)\n",
    "                        for i, event in enumerate(eventlist):\n",
    "                            if i >= min_event_count:\n",
    "                                break\n",
    "\n",
    "                            if event['event']['event_type'] == 'set_text':\n",
    "                                num_set_text[1] += 1\n",
    "\n",
    "                            from_state = event['from']\n",
    "                            to_state = event['to']\n",
    "\n",
    "                            if from_state in state2activity_2:\n",
    "                                reached_activities[1].add(state2activity_2[from_state])\n",
    "                                if is_valid_activity(app_id, state2activity_2[from_state]):\n",
    "                                    covered_states[1].add(from_state)\n",
    "                            if to_state in state2activity_2:\n",
    "                                reached_activities[1].add(state2activity_2[to_state])\n",
    "                                if is_valid_activity(app_id, state2activity_2[to_state]):\n",
    "                                    covered_states[1].add(to_state)\n",
    "\n",
    "                    with open(os.path.join(output_dir_3, 'app_info.json')) as f:\n",
    "                        package_name = json.load(f)['app_package']\n",
    "\n",
    "                    with open(os.path.join(output_dir_3, 'eventlist.json')) as f:\n",
    "                        eventlist = json.load(f)\n",
    "                        for i, event in enumerate(eventlist):\n",
    "                            if i >= min_event_count:\n",
    "                                break\n",
    "\n",
    "                            if event['event']['event_type'] == 'set_text':\n",
    "                                num_set_text[2] += 1\n",
    "\n",
    "                            from_state = event['from']\n",
    "                            to_state = event['to']\n",
    "\n",
    "                            if from_state in state2activity_3:\n",
    "                                reached_activities[2].add(state2activity_3[from_state])\n",
    "                                if is_valid_activity(app_id, state2activity_3[from_state]):\n",
    "                                    covered_states[2].add(from_state)\n",
    "                            if to_state in state2activity_3:\n",
    "                                reached_activities[2].add(state2activity_3[to_state])\n",
    "                                if is_valid_activity(app_id, state2activity_3[to_state]):\n",
    "                                    covered_states[2].add(to_state)\n",
    "\n",
    "\n",
    "                internal_activities_1 = [a for a in reached_activities[0] if is_valid_activity(app_id, a)]\n",
    "                internal_activities_2 = [a for a in reached_activities[1] if is_valid_activity(app_id, a)]\n",
    "                internal_activities_3 = [a for a in reached_activities[2] if is_valid_activity(app_id, a)]\n",
    "                \n",
    "                internal_activities = internal_activities_1\n",
    "\n",
    "                ra = reached_activities[0]\n",
    "                cs = covered_states[0]\n",
    "                nst = num_set_text[0]\n",
    "\n",
    "                if INCLUDE_MULTI_RUN_RESULTS:\n",
    "                    if len(internal_activities_2) > len(internal_activities_1) and len(internal_activities_2) > internal_activities_3:\n",
    "                        ra = reached_activities[1]\n",
    "                        cs = covered_states[1]\n",
    "                        nst = num_set_text[1]\n",
    "                        internal_activities = internal_activities_2\n",
    "                    elif len(internal_activities_3) > len(internal_activities_1) and len(internal_activities_3) > internal_activities_2:\n",
    "                        ra = reached_activities[2]\n",
    "                        cs = covered_states[2]\n",
    "                        nst = num_set_text[2]\n",
    "                        internal_activities = internal_activities_3\n",
    "\n",
    "                \n",
    "                results.append({\n",
    "                    'technique': 'STEM+DroidFiller',\n",
    "                    'app': app_id,\n",
    "                    'num_all_activities': len(activities_map[app_id]['raw']),\n",
    "                    'num_nodes': min_event_count,\n",
    "                    # 'num_internal_activities': len(internal_activities),\n",
    "                    'num_reached_activities': len(ra),\n",
    "                    'num_internal_activities': len(internal_activities),\n",
    "                    'num_covered_states': len(cs),\n",
    "                    'reached_activities': list(ra),\n",
    "                    'internal_activities': internal_activities,\n",
    "                    # 'dynamic_coverage': summary['dynamic_coverage_auc'],\n",
    "                    'num_set_text': nst\n",
    "                })\n",
    "\n",
    "                for i in range(3):\n",
    "                    ia = internal_activities_1\n",
    "                    if i == 1:\n",
    "                        ia = internal_activities_2\n",
    "                    elif i == 2:\n",
    "                        ia = internal_activities_3\n",
    "                    full_results.append({\n",
    "                        'technique': 'STEM+DroidFiller',\n",
    "                        'app': app_id,\n",
    "                        'num_all_activities': len(activities_map[app_id]['raw']),\n",
    "                        'num_nodes': min_event_count,\n",
    "                        # 'num_internal_activities': len(internal_activities),\n",
    "                        'num_reached_activities': len(reached_activities[i]),\n",
    "                        'num_internal_activities': len(ia),\n",
    "                        'num_covered_states': len(covered_states[i]),\n",
    "                        'reached_activities': list(reached_activities[i]),\n",
    "                        'internal_activities': ia,\n",
    "                        # 'dynamic_coverage': summary['dynamic_coverage_auc'],\n",
    "                        'num_set_text': nst\n",
    "                    })\n",
    "\n",
    "                \n",
    "                num_set_text = [0, 0, 0]\n",
    "                covered_states = [set(), set(), set()]\n",
    "\n",
    "                with open(f'./stem_output_context/{app_id}/eventlist.json') as f:\n",
    "                    eventlist_context = json.load(f)\n",
    "                    for i, event in enumerate(eventlist_context):\n",
    "                        if i >= min_event_count:\n",
    "                            break\n",
    "\n",
    "                        if event['event']['event_type'] == 'set_text':\n",
    "                            num_set_text[0] += 1\n",
    "                        \n",
    "                        from_state = event['from']\n",
    "                        to_state = event['to']\n",
    "\n",
    "                        if from_state in state2activity_context:\n",
    "                            reached_activities_context[0].add(state2activity_context[from_state])\n",
    "                            if is_valid_activity(app_id, state2activity_context[from_state]):\n",
    "                                covered_states[0].add(from_state)\n",
    "                        if to_state in state2activity_context:\n",
    "                            reached_activities_context[0].add(state2activity_context[to_state])\n",
    "                            if is_valid_activity(app_id, state2activity_context[to_state]):\n",
    "                                covered_states[0].add(to_state)\n",
    "\n",
    "                        time_results.append({\n",
    "                            'technique': 'Context',\n",
    "                            'app_id': app_id,\n",
    "                            'event_no': i+1,\n",
    "                            'num_covered_activities': len([a for a in reached_activities_context[0] if is_valid_activity(app_id, a)]),\n",
    "                        })\n",
    "\n",
    "\n",
    "                if INCLUDE_MULTI_RUN_RESULTS:\n",
    "                    with open(f'./stem_output_context_2/{app_id}/eventlist.json') as f:\n",
    "                        eventlist_context = json.load(f)\n",
    "                        for i, event in enumerate(eventlist_context):\n",
    "                            if i >= min_event_count:\n",
    "                                break\n",
    "\n",
    "                            if event['event']['event_type'] == 'set_text':\n",
    "                                num_set_text[1] += 1\n",
    "                            \n",
    "                            from_state = event['from']\n",
    "                            to_state = event['to']\n",
    "\n",
    "                            if from_state in state2activity_context_2:\n",
    "                                reached_activities_context[1].add(state2activity_context_2[from_state])\n",
    "                                if is_valid_activity(app_id, state2activity_context_2[from_state]):\n",
    "                                    covered_states[1].add(from_state)\n",
    "                            if to_state in state2activity_context_2:\n",
    "                                reached_activities_context[1].add(state2activity_context_2[to_state])\n",
    "                                if is_valid_activity(app_id, state2activity_context_2[to_state]):\n",
    "                                    covered_states[1].add(to_state)\n",
    "\n",
    "                    with open(f'./stem_output_context_3/{app_id}/eventlist.json') as f:\n",
    "                        eventlist_context = json.load(f)\n",
    "                        for i, event in enumerate(eventlist_context):\n",
    "                            if i >= min_event_count:\n",
    "                                break\n",
    "\n",
    "                            if event['event']['event_type'] == 'set_text':\n",
    "                                num_set_text[2] += 1\n",
    "                            \n",
    "                            from_state = event['from']\n",
    "                            to_state = event['to']\n",
    "\n",
    "                            if from_state in state2activity_context_3:\n",
    "                                reached_activities_context[2].add(state2activity_context_3[from_state])\n",
    "                                if is_valid_activity(app_id, state2activity_context_3[from_state]):\n",
    "                                    covered_states[2].add(from_state)\n",
    "                            if to_state in state2activity_context_3:\n",
    "                                reached_activities_context[2].add(state2activity_context_3[to_state])\n",
    "                                if is_valid_activity(app_id, state2activity_context_3[to_state]):\n",
    "                                    covered_states[2].add(to_state)\n",
    "\n",
    "\n",
    "                internal_activities_1 = [a for a in reached_activities_context[0] if is_valid_activity(app_id, a)]\n",
    "                internal_activities_2 = [a for a in reached_activities_context[1] if is_valid_activity(app_id, a)]\n",
    "                internal_activities_3 = [a for a in reached_activities_context[2] if is_valid_activity(app_id, a)]\n",
    "\n",
    "                internal_activities = internal_activities_1\n",
    "\n",
    "                ra_context = reached_activities_context[0]\n",
    "                cs_context = covered_states[0]\n",
    "                nst_context = num_set_text[0]\n",
    "\n",
    "                if INCLUDE_MULTI_RUN_RESULTS:\n",
    "                    if len(internal_activities_2) > len(internal_activities_1) and len(internal_activities_2) > len(internal_activities_3):\n",
    "                        ra_context = reached_activities_context[1]\n",
    "                        cs_context = covered_states[1]\n",
    "                        nst_context = num_set_text[1]\n",
    "                        internal_activities = internal_activities_2\n",
    "\n",
    "\n",
    "                    if len(internal_activities_3) > len(internal_activities_1) and len(internal_activities_3) > len(internal_activities_2):\n",
    "                        ra_context = reached_activities_context[2]\n",
    "                        cs_context = covered_states[2]\n",
    "                        nst_context = num_set_text[2]\n",
    "                        internal_activities = internal_activities_3\n",
    "\n",
    "\n",
    "                print(app_id)\n",
    "                print('reached_activities (DroidFiller)', ra, f'({len(ra)})')\n",
    "                print('reached_activities (Context)', ra_context, f'({len(ra_context)})')\n",
    "                print('internal_activities (DroidFiller)', [a for a in ra if is_valid_activity(app_id, a)], f'({len([a for a in ra if is_valid_activity(app_id, a)])})')\n",
    "                print('internal_activities (Context)', [a for a in ra_context if is_valid_activity(app_id, a)], f'({len([a for a in ra_context if is_valid_activity(app_id, a)])})')\n",
    "                print()\n",
    "                print('---')\n",
    "                print()\n",
    "                \n",
    "                results.append({\n",
    "                    'technique': 'STEM+Context',\n",
    "                    'app': app_id,\n",
    "                    'num_all_activities': len(activities_map[app_id]['raw']),\n",
    "                    'num_nodes': min_event_count,\n",
    "                    # 'num_internal_activities': len(internal_activities_context),\n",
    "                    'num_reached_activities': len(ra_context),\n",
    "                    'num_internal_activities': len(internal_activities),\n",
    "                    'num_covered_states': len(cs_context),\n",
    "                    'reached_activities': list(ra_context),\n",
    "                    'internal_activities': internal_activities,\n",
    "                    # 'dynamic_coverage': summary_context['dynamic_coverage_auc'],\n",
    "                    'num_set_text': nst_context\n",
    "                })\n",
    "\n",
    "                for i in range(3):\n",
    "                    ia = internal_activities_1\n",
    "                    if i == 1:\n",
    "                        ia = internal_activities_2\n",
    "                    elif i == 2:\n",
    "                        ia = internal_activities_3\n",
    "                    full_results.append({\n",
    "                        'technique': 'STEM+Context',\n",
    "                        'app': app_id,\n",
    "                        'num_all_activities': len(activities_map[app_id]['raw']),\n",
    "                        'num_nodes': min_event_count,\n",
    "                        # 'num_internal_activities': len(internal_activities),\n",
    "                        'num_reached_activities': len(reached_activities_context[i]),\n",
    "                        'num_internal_activities': len(ia),\n",
    "                        'num_covered_states': len(covered_states[i]),\n",
    "                        'reached_activities': list(reached_activities_context[i]),\n",
    "                        'internal_activities': ia,\n",
    "                        # 'dynamic_coverage': summary['dynamic_coverage_auc'],\n",
    "                        'num_set_text': nst\n",
    "                    })\n",
    "                \n",
    "\n",
    "print('Missing: {}'.format(missing))\n",
    "# missing: phone"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>technique</th>\n",
       "      <th>app</th>\n",
       "      <th>num_all_activities</th>\n",
       "      <th>num_nodes</th>\n",
       "      <th>num_reached_activities</th>\n",
       "      <th>num_internal_activities</th>\n",
       "      <th>num_covered_states</th>\n",
       "      <th>reached_activities</th>\n",
       "      <th>internal_activities</th>\n",
       "      <th>num_set_text</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>STEM+DroidFiller</td>\n",
       "      <td>oss.krtirtho.spotube_31</td>\n",
       "      <td>7</td>\n",
       "      <td>1188</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>190</td>\n",
       "      <td>[HomeDashboardActivity, Settings$WifiSettingsA...</td>\n",
       "      <td>[AudioServiceActivity]</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>STEM+Context</td>\n",
       "      <td>oss.krtirtho.spotube_31</td>\n",
       "      <td>7</td>\n",
       "      <td>1188</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>197</td>\n",
       "      <td>[FeedbackAlohaActivity, RequestIgnoreBatteryOp...</td>\n",
       "      <td>[AudioServiceActivity]</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>STEM+DroidFiller</td>\n",
       "      <td>org.asafonov.monly_47</td>\n",
       "      <td>1</td>\n",
       "      <td>896</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>152</td>\n",
       "      <td>[LauncherActivity, MainActivity]</td>\n",
       "      <td>[MainActivity]</td>\n",
       "      <td>238</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>STEM+Context</td>\n",
       "      <td>org.asafonov.monly_47</td>\n",
       "      <td>1</td>\n",
       "      <td>896</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>160</td>\n",
       "      <td>[LauncherActivity, MainActivity]</td>\n",
       "      <td>[MainActivity]</td>\n",
       "      <td>265</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>STEM+DroidFiller</td>\n",
       "      <td>lying.fengfeng.foodrecords_1</td>\n",
       "      <td>2</td>\n",
       "      <td>386</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>93</td>\n",
       "      <td>[LauncherActivity, MainActivity, AppErrorDialo...</td>\n",
       "      <td>[MainActivity]</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>STEM+Context</td>\n",
       "      <td>lying.fengfeng.foodrecords_1</td>\n",
       "      <td>2</td>\n",
       "      <td>386</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>78</td>\n",
       "      <td>[LauncherActivity, MainActivity]</td>\n",
       "      <td>[MainActivity]</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>STEM+DroidFiller</td>\n",
       "      <td>familyfinance</td>\n",
       "      <td>30</td>\n",
       "      <td>1689</td>\n",
       "      <td>31</td>\n",
       "      <td>27</td>\n",
       "      <td>181</td>\n",
       "      <td>[IncomeOperationActivity, ExpenseArticleEditAc...</td>\n",
       "      <td>[IncomeOperationActivity, ExpenseArticleEditAc...</td>\n",
       "      <td>82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>STEM+Context</td>\n",
       "      <td>familyfinance</td>\n",
       "      <td>30</td>\n",
       "      <td>1689</td>\n",
       "      <td>22</td>\n",
       "      <td>20</td>\n",
       "      <td>187</td>\n",
       "      <td>[ExpenseArticleEditActivity, ExpenseOperationA...</td>\n",
       "      <td>[ExpenseArticleEditActivity, ExpenseOperationA...</td>\n",
       "      <td>57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>STEM+DroidFiller</td>\n",
       "      <td>org.tasks_130909</td>\n",
       "      <td>46</td>\n",
       "      <td>1775</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "      <td>434</td>\n",
       "      <td>[SortSettingsActivity, Camera, GoogleTTSActivi...</td>\n",
       "      <td>[SortSettingsActivity, CustomRecurrenceActivit...</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>STEM+Context</td>\n",
       "      <td>org.tasks_130909</td>\n",
       "      <td>46</td>\n",
       "      <td>1775</td>\n",
       "      <td>10</td>\n",
       "      <td>4</td>\n",
       "      <td>22</td>\n",
       "      <td>[SortSettingsActivity, ConversationComposer, M...</td>\n",
       "      <td>[SortSettingsActivity, LocationPickerActivity,...</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>STEM+DroidFiller</td>\n",
       "      <td>com.ichi2.anki_21803300</td>\n",
       "      <td>29</td>\n",
       "      <td>1464</td>\n",
       "      <td>30</td>\n",
       "      <td>15</td>\n",
       "      <td>297</td>\n",
       "      <td>[ResolverActivity, MultimediaEditFieldActivity...</td>\n",
       "      <td>[MultimediaEditFieldActivity, NoteEditor, Card...</td>\n",
       "      <td>90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>STEM+Context</td>\n",
       "      <td>com.ichi2.anki_21803300</td>\n",
       "      <td>29</td>\n",
       "      <td>1464</td>\n",
       "      <td>16</td>\n",
       "      <td>11</td>\n",
       "      <td>229</td>\n",
       "      <td>[ResolverActivity, SingleFragmentActivity, Sha...</td>\n",
       "      <td>[SingleFragmentActivity, SharedDecksActivity, ...</td>\n",
       "      <td>311</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>STEM+DroidFiller</td>\n",
       "      <td>luci.sixsixsix.powerampache2.fdroid_59</td>\n",
       "      <td>1</td>\n",
       "      <td>1450</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>120</td>\n",
       "      <td>[ComposeActivityGmailExternal, ShareActivity, ...</td>\n",
       "      <td>[MainActivity]</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>STEM+Context</td>\n",
       "      <td>luci.sixsixsix.powerampache2.fdroid_59</td>\n",
       "      <td>1</td>\n",
       "      <td>1450</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>117</td>\n",
       "      <td>[ComposeActivityGmailExternal, ShareActivity, ...</td>\n",
       "      <td>[MainActivity]</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>STEM+DroidFiller</td>\n",
       "      <td>moe.dic1911.urlsanitizer_30</td>\n",
       "      <td>4</td>\n",
       "      <td>1671</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>33</td>\n",
       "      <td>[LauncherActivity, MainActivity, PrivacyRedire...</td>\n",
       "      <td>[MainActivity, PrivacyRedirectActivity, EntryL...</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>STEM+Context</td>\n",
       "      <td>moe.dic1911.urlsanitizer_30</td>\n",
       "      <td>4</td>\n",
       "      <td>1671</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>31</td>\n",
       "      <td>[LauncherActivity, MainActivity, PrivacyRedire...</td>\n",
       "      <td>[MainActivity, PrivacyRedirectActivity, EntryL...</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>STEM+DroidFiller</td>\n",
       "      <td>com.nextcloud.talk2_190000190</td>\n",
       "      <td>30</td>\n",
       "      <td>1537</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>85</td>\n",
       "      <td>[LauncherActivity, SBrowserMainActivity, Serve...</td>\n",
       "      <td>[ServerSelectionActivity, WebViewLoginActivity]</td>\n",
       "      <td>125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>STEM+Context</td>\n",
       "      <td>com.nextcloud.talk2_190000190</td>\n",
       "      <td>30</td>\n",
       "      <td>1537</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>[LauncherActivity, SBrowserMainActivity, Serve...</td>\n",
       "      <td>[ServerSelectionActivity]</td>\n",
       "      <td>172</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>STEM+DroidFiller</td>\n",
       "      <td>com.moimob.drinkable_15000</td>\n",
       "      <td>1</td>\n",
       "      <td>469</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>24</td>\n",
       "      <td>[LauncherActivity, MainActivity]</td>\n",
       "      <td>[MainActivity]</td>\n",
       "      <td>63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>STEM+Context</td>\n",
       "      <td>com.moimob.drinkable_15000</td>\n",
       "      <td>1</td>\n",
       "      <td>469</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>18</td>\n",
       "      <td>[LauncherActivity, MainActivity]</td>\n",
       "      <td>[MainActivity]</td>\n",
       "      <td>53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>STEM+DroidFiller</td>\n",
       "      <td>com.money.manager.ex_1032</td>\n",
       "      <td>48</td>\n",
       "      <td>1602</td>\n",
       "      <td>16</td>\n",
       "      <td>13</td>\n",
       "      <td>982</td>\n",
       "      <td>[PayeeActivity, SyncPreferencesActivity, Searc...</td>\n",
       "      <td>[PayeeActivity, SyncPreferencesActivity, Searc...</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>STEM+Context</td>\n",
       "      <td>com.money.manager.ex_1032</td>\n",
       "      <td>48</td>\n",
       "      <td>1602</td>\n",
       "      <td>20</td>\n",
       "      <td>15</td>\n",
       "      <td>962</td>\n",
       "      <td>[ConversationsListActivity, MainActivity, Sele...</td>\n",
       "      <td>[MainActivity, SelectDatabaseActivity, General...</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>STEM+DroidFiller</td>\n",
       "      <td>aeroflot</td>\n",
       "      <td>33</td>\n",
       "      <td>1597</td>\n",
       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "      <td>550</td>\n",
       "      <td>[BookingDetailsActivity, GiftCertificateActivi...</td>\n",
       "      <td>[BookingDetailsActivity, GiftCertificateActivi...</td>\n",
       "      <td>66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>STEM+Context</td>\n",
       "      <td>aeroflot</td>\n",
       "      <td>33</td>\n",
       "      <td>1597</td>\n",
       "      <td>9</td>\n",
       "      <td>8</td>\n",
       "      <td>554</td>\n",
       "      <td>[BookingDetailsActivity, GiftCertificateActivi...</td>\n",
       "      <td>[BookingDetailsActivity, GiftCertificateActivi...</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           technique                                     app  \\\n",
       "0   STEM+DroidFiller                 oss.krtirtho.spotube_31   \n",
       "1       STEM+Context                 oss.krtirtho.spotube_31   \n",
       "2   STEM+DroidFiller                   org.asafonov.monly_47   \n",
       "3       STEM+Context                   org.asafonov.monly_47   \n",
       "4   STEM+DroidFiller            lying.fengfeng.foodrecords_1   \n",
       "5       STEM+Context            lying.fengfeng.foodrecords_1   \n",
       "6   STEM+DroidFiller                           familyfinance   \n",
       "7       STEM+Context                           familyfinance   \n",
       "8   STEM+DroidFiller                        org.tasks_130909   \n",
       "9       STEM+Context                        org.tasks_130909   \n",
       "10  STEM+DroidFiller                 com.ichi2.anki_21803300   \n",
       "11      STEM+Context                 com.ichi2.anki_21803300   \n",
       "12  STEM+DroidFiller  luci.sixsixsix.powerampache2.fdroid_59   \n",
       "13      STEM+Context  luci.sixsixsix.powerampache2.fdroid_59   \n",
       "14  STEM+DroidFiller             moe.dic1911.urlsanitizer_30   \n",
       "15      STEM+Context             moe.dic1911.urlsanitizer_30   \n",
       "16  STEM+DroidFiller           com.nextcloud.talk2_190000190   \n",
       "17      STEM+Context           com.nextcloud.talk2_190000190   \n",
       "18  STEM+DroidFiller              com.moimob.drinkable_15000   \n",
       "19      STEM+Context              com.moimob.drinkable_15000   \n",
       "20  STEM+DroidFiller               com.money.manager.ex_1032   \n",
       "21      STEM+Context               com.money.manager.ex_1032   \n",
       "22  STEM+DroidFiller                                aeroflot   \n",
       "23      STEM+Context                                aeroflot   \n",
       "\n",
       "    num_all_activities  num_nodes  num_reached_activities  \\\n",
       "0                    7       1188                       9   \n",
       "1                    7       1188                       8   \n",
       "2                    1        896                       2   \n",
       "3                    1        896                       2   \n",
       "4                    2        386                       3   \n",
       "5                    2        386                       2   \n",
       "6                   30       1689                      31   \n",
       "7                   30       1689                      22   \n",
       "8                   46       1775                       8   \n",
       "9                   46       1775                      10   \n",
       "10                  29       1464                      30   \n",
       "11                  29       1464                      16   \n",
       "12                   1       1450                       6   \n",
       "13                   1       1450                       6   \n",
       "14                   4       1671                       4   \n",
       "15                   4       1671                       4   \n",
       "16                  30       1537                       4   \n",
       "17                  30       1537                       3   \n",
       "18                   1        469                       2   \n",
       "19                   1        469                       2   \n",
       "20                  48       1602                      16   \n",
       "21                  48       1602                      20   \n",
       "22                  33       1597                      11   \n",
       "23                  33       1597                       9   \n",
       "\n",
       "    num_internal_activities  num_covered_states  \\\n",
       "0                         1                 190   \n",
       "1                         1                 197   \n",
       "2                         1                 152   \n",
       "3                         1                 160   \n",
       "4                         1                  93   \n",
       "5                         1                  78   \n",
       "6                        27                 181   \n",
       "7                        20                 187   \n",
       "8                         4                 434   \n",
       "9                         4                  22   \n",
       "10                       15                 297   \n",
       "11                       11                 229   \n",
       "12                        1                 120   \n",
       "13                        1                 117   \n",
       "14                        3                  33   \n",
       "15                        3                  31   \n",
       "16                        2                  85   \n",
       "17                        1                   7   \n",
       "18                        1                  24   \n",
       "19                        1                  18   \n",
       "20                       13                 982   \n",
       "21                       15                 962   \n",
       "22                       10                 550   \n",
       "23                        8                 554   \n",
       "\n",
       "                                   reached_activities  \\\n",
       "0   [HomeDashboardActivity, Settings$WifiSettingsA...   \n",
       "1   [FeedbackAlohaActivity, RequestIgnoreBatteryOp...   \n",
       "2                    [LauncherActivity, MainActivity]   \n",
       "3                    [LauncherActivity, MainActivity]   \n",
       "4   [LauncherActivity, MainActivity, AppErrorDialo...   \n",
       "5                    [LauncherActivity, MainActivity]   \n",
       "6   [IncomeOperationActivity, ExpenseArticleEditAc...   \n",
       "7   [ExpenseArticleEditActivity, ExpenseOperationA...   \n",
       "8   [SortSettingsActivity, Camera, GoogleTTSActivi...   \n",
       "9   [SortSettingsActivity, ConversationComposer, M...   \n",
       "10  [ResolverActivity, MultimediaEditFieldActivity...   \n",
       "11  [ResolverActivity, SingleFragmentActivity, Sha...   \n",
       "12  [ComposeActivityGmailExternal, ShareActivity, ...   \n",
       "13  [ComposeActivityGmailExternal, ShareActivity, ...   \n",
       "14  [LauncherActivity, MainActivity, PrivacyRedire...   \n",
       "15  [LauncherActivity, MainActivity, PrivacyRedire...   \n",
       "16  [LauncherActivity, SBrowserMainActivity, Serve...   \n",
       "17  [LauncherActivity, SBrowserMainActivity, Serve...   \n",
       "18                   [LauncherActivity, MainActivity]   \n",
       "19                   [LauncherActivity, MainActivity]   \n",
       "20  [PayeeActivity, SyncPreferencesActivity, Searc...   \n",
       "21  [ConversationsListActivity, MainActivity, Sele...   \n",
       "22  [BookingDetailsActivity, GiftCertificateActivi...   \n",
       "23  [BookingDetailsActivity, GiftCertificateActivi...   \n",
       "\n",
       "                                  internal_activities  num_set_text  \n",
       "0                              [AudioServiceActivity]            12  \n",
       "1                              [AudioServiceActivity]            14  \n",
       "2                                      [MainActivity]           238  \n",
       "3                                      [MainActivity]           265  \n",
       "4                                      [MainActivity]             2  \n",
       "5                                      [MainActivity]             2  \n",
       "6   [IncomeOperationActivity, ExpenseArticleEditAc...            82  \n",
       "7   [ExpenseArticleEditActivity, ExpenseOperationA...            57  \n",
       "8   [SortSettingsActivity, CustomRecurrenceActivit...             6  \n",
       "9   [SortSettingsActivity, LocationPickerActivity,...            10  \n",
       "10  [MultimediaEditFieldActivity, NoteEditor, Card...            90  \n",
       "11  [SingleFragmentActivity, SharedDecksActivity, ...           311  \n",
       "12                                     [MainActivity]             4  \n",
       "13                                     [MainActivity]            12  \n",
       "14  [MainActivity, PrivacyRedirectActivity, EntryL...             6  \n",
       "15  [MainActivity, PrivacyRedirectActivity, EntryL...             4  \n",
       "16    [ServerSelectionActivity, WebViewLoginActivity]           125  \n",
       "17                          [ServerSelectionActivity]           172  \n",
       "18                                     [MainActivity]            63  \n",
       "19                                     [MainActivity]            53  \n",
       "20  [PayeeActivity, SyncPreferencesActivity, Searc...            24  \n",
       "21  [MainActivity, SelectDatabaseActivity, General...            19  \n",
       "22  [BookingDetailsActivity, GiftCertificateActivi...            66  \n",
       "23  [BookingDetailsActivity, GiftCertificateActivi...            35  "
      ]
     },
     "execution_count": 131,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "result_df = pd.DataFrame(results)\n",
    "result_df.to_csv('stem_integration.csv', index=False)\n",
    "result_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>technique</th>\n",
       "      <th>app</th>\n",
       "      <th>num_all_activities</th>\n",
       "      <th>num_nodes</th>\n",
       "      <th>num_reached_activities</th>\n",
       "      <th>num_internal_activities</th>\n",
       "      <th>num_covered_states</th>\n",
       "      <th>reached_activities</th>\n",
       "      <th>internal_activities</th>\n",
       "      <th>num_set_text</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>STEM+DroidFiller</td>\n",
       "      <td>oss.krtirtho.spotube_31</td>\n",
       "      <td>7</td>\n",
       "      <td>1188</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>190</td>\n",
       "      <td>[HomeDashboardActivity, Settings$WifiSettingsA...</td>\n",
       "      <td>[AudioServiceActivity]</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>STEM+DroidFiller</td>\n",
       "      <td>oss.krtirtho.spotube_31</td>\n",
       "      <td>7</td>\n",
       "      <td>1188</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>124</td>\n",
       "      <td>[HomeDashboardActivity, RequestIgnoreBatteryOp...</td>\n",
       "      <td>[AudioServiceActivity]</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>STEM+DroidFiller</td>\n",
       "      <td>oss.krtirtho.spotube_31</td>\n",
       "      <td>7</td>\n",
       "      <td>1188</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>155</td>\n",
       "      <td>[HomeDashboardActivity, ResolverActivity, Requ...</td>\n",
       "      <td>[AudioServiceActivity]</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>STEM+Context</td>\n",
       "      <td>oss.krtirtho.spotube_31</td>\n",
       "      <td>7</td>\n",
       "      <td>1188</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>197</td>\n",
       "      <td>[FeedbackAlohaActivity, RequestIgnoreBatteryOp...</td>\n",
       "      <td>[AudioServiceActivity]</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>STEM+Context</td>\n",
       "      <td>oss.krtirtho.spotube_31</td>\n",
       "      <td>7</td>\n",
       "      <td>1188</td>\n",
       "      <td>17</td>\n",
       "      <td>1</td>\n",
       "      <td>142</td>\n",
       "      <td>[NfcAntennaGuideDialog, FreActivity, HomeDashb...</td>\n",
       "      <td>[AudioServiceActivity]</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>STEM+DroidFiller</td>\n",
       "      <td>aeroflot</td>\n",
       "      <td>33</td>\n",
       "      <td>1597</td>\n",
       "      <td>18</td>\n",
       "      <td>10</td>\n",
       "      <td>615</td>\n",
       "      <td>[ContactPickerActivity, ResolverActivity, Book...</td>\n",
       "      <td>[BookingDetailsActivity, GiftCertificateActivi...</td>\n",
       "      <td>66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>STEM+DroidFiller</td>\n",
       "      <td>aeroflot</td>\n",
       "      <td>33</td>\n",
       "      <td>1597</td>\n",
       "      <td>9</td>\n",
       "      <td>8</td>\n",
       "      <td>586</td>\n",
       "      <td>[BookingDetailsActivity, GiftCertificateActivi...</td>\n",
       "      <td>[BookingDetailsActivity, GiftCertificateActivi...</td>\n",
       "      <td>66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>STEM+Context</td>\n",
       "      <td>aeroflot</td>\n",
       "      <td>33</td>\n",
       "      <td>1597</td>\n",
       "      <td>9</td>\n",
       "      <td>8</td>\n",
       "      <td>554</td>\n",
       "      <td>[BookingDetailsActivity, GiftCertificateActivi...</td>\n",
       "      <td>[BookingDetailsActivity, GiftCertificateActivi...</td>\n",
       "      <td>66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>STEM+Context</td>\n",
       "      <td>aeroflot</td>\n",
       "      <td>33</td>\n",
       "      <td>1597</td>\n",
       "      <td>10</td>\n",
       "      <td>8</td>\n",
       "      <td>479</td>\n",
       "      <td>[ResolverActivity, BookingDetailsActivity, Gif...</td>\n",
       "      <td>[BookingDetailsActivity, GiftCertificateActivi...</td>\n",
       "      <td>66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>STEM+Context</td>\n",
       "      <td>aeroflot</td>\n",
       "      <td>33</td>\n",
       "      <td>1597</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>585</td>\n",
       "      <td>[BookingDetailsActivity, CitySearchActivity, L...</td>\n",
       "      <td>[BookingDetailsActivity, CitySearchActivity, B...</td>\n",
       "      <td>66</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>72 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           technique                      app  num_all_activities  num_nodes  \\\n",
       "0   STEM+DroidFiller  oss.krtirtho.spotube_31                   7       1188   \n",
       "1   STEM+DroidFiller  oss.krtirtho.spotube_31                   7       1188   \n",
       "2   STEM+DroidFiller  oss.krtirtho.spotube_31                   7       1188   \n",
       "3       STEM+Context  oss.krtirtho.spotube_31                   7       1188   \n",
       "4       STEM+Context  oss.krtirtho.spotube_31                   7       1188   \n",
       "..               ...                      ...                 ...        ...   \n",
       "67  STEM+DroidFiller                 aeroflot                  33       1597   \n",
       "68  STEM+DroidFiller                 aeroflot                  33       1597   \n",
       "69      STEM+Context                 aeroflot                  33       1597   \n",
       "70      STEM+Context                 aeroflot                  33       1597   \n",
       "71      STEM+Context                 aeroflot                  33       1597   \n",
       "\n",
       "    num_reached_activities  num_internal_activities  num_covered_states  \\\n",
       "0                        9                        1                 190   \n",
       "1                        5                        1                 124   \n",
       "2                        8                        1                 155   \n",
       "3                        8                        1                 197   \n",
       "4                       17                        1                 142   \n",
       "..                     ...                      ...                 ...   \n",
       "67                      18                       10                 615   \n",
       "68                       9                        8                 586   \n",
       "69                       9                        8                 554   \n",
       "70                      10                        8                 479   \n",
       "71                       5                        4                 585   \n",
       "\n",
       "                                   reached_activities  \\\n",
       "0   [HomeDashboardActivity, Settings$WifiSettingsA...   \n",
       "1   [HomeDashboardActivity, RequestIgnoreBatteryOp...   \n",
       "2   [HomeDashboardActivity, ResolverActivity, Requ...   \n",
       "3   [FeedbackAlohaActivity, RequestIgnoreBatteryOp...   \n",
       "4   [NfcAntennaGuideDialog, FreActivity, HomeDashb...   \n",
       "..                                                ...   \n",
       "67  [ContactPickerActivity, ResolverActivity, Book...   \n",
       "68  [BookingDetailsActivity, GiftCertificateActivi...   \n",
       "69  [BookingDetailsActivity, GiftCertificateActivi...   \n",
       "70  [ResolverActivity, BookingDetailsActivity, Gif...   \n",
       "71  [BookingDetailsActivity, CitySearchActivity, L...   \n",
       "\n",
       "                                  internal_activities  num_set_text  \n",
       "0                              [AudioServiceActivity]            12  \n",
       "1                              [AudioServiceActivity]            12  \n",
       "2                              [AudioServiceActivity]            12  \n",
       "3                              [AudioServiceActivity]            12  \n",
       "4                              [AudioServiceActivity]            12  \n",
       "..                                                ...           ...  \n",
       "67  [BookingDetailsActivity, GiftCertificateActivi...            66  \n",
       "68  [BookingDetailsActivity, GiftCertificateActivi...            66  \n",
       "69  [BookingDetailsActivity, GiftCertificateActivi...            66  \n",
       "70  [BookingDetailsActivity, GiftCertificateActivi...            66  \n",
       "71  [BookingDetailsActivity, CitySearchActivity, B...            66  \n",
       "\n",
       "[72 rows x 10 columns]"
      ]
     },
     "execution_count": 132,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "full_result_df = pd.DataFrame(full_results)\n",
    "full_result_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"8\" halign=\"left\">num_reached_activities</th>\n",
       "      <th colspan=\"8\" halign=\"left\">num_covered_states</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>technique</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>STEM+Context</th>\n",
       "      <td>12.0</td>\n",
       "      <td>8.666667</td>\n",
       "      <td>7.113794</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.75</td>\n",
       "      <td>7.0</td>\n",
       "      <td>11.50</td>\n",
       "      <td>22.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>230.00</td>\n",
       "      <td>301.843126</td>\n",
       "      <td>7.0</td>\n",
       "      <td>28.75</td>\n",
       "      <td>157.0</td>\n",
       "      <td>231.00</td>\n",
       "      <td>1055.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>STEM+DroidFiller</th>\n",
       "      <td>12.0</td>\n",
       "      <td>10.666667</td>\n",
       "      <td>10.368951</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.75</td>\n",
       "      <td>7.0</td>\n",
       "      <td>12.25</td>\n",
       "      <td>31.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>283.75</td>\n",
       "      <td>300.631192</td>\n",
       "      <td>33.0</td>\n",
       "      <td>91.00</td>\n",
       "      <td>199.0</td>\n",
       "      <td>347.75</td>\n",
       "      <td>1092.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 num_reached_activities                                        \\\n",
       "                                  count       mean        std  min   25%  50%   \n",
       "technique                                                                       \n",
       "STEM+Context                       12.0   8.666667   7.113794  2.0  2.75  7.0   \n",
       "STEM+DroidFiller                   12.0  10.666667  10.368951  2.0  3.75  7.0   \n",
       "\n",
       "                              num_covered_states                            \\\n",
       "                    75%   max              count    mean         std   min   \n",
       "technique                                                                    \n",
       "STEM+Context      11.50  22.0               12.0  230.00  301.843126   7.0   \n",
       "STEM+DroidFiller  12.25  31.0               12.0  283.75  300.631192  33.0   \n",
       "\n",
       "                                                \n",
       "                    25%    50%     75%     max  \n",
       "technique                                       \n",
       "STEM+Context      28.75  157.0  231.00  1055.0  \n",
       "STEM+DroidFiller  91.00  199.0  347.75  1092.0  "
      ]
     },
     "execution_count": 114,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result_df.groupby('technique').describe()[['num_reached_activities', 'num_covered_states']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "WilcoxonResult(statistic=31.0, pvalue=0.015048201117169315)"
      ]
     },
     "execution_count": 133,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import scipy.stats as stats\n",
    "\n",
    "stats.wilcoxon(full_result_df[full_result_df.technique == 'STEM+Context']['num_internal_activities'], full_result_df[full_result_df.technique == 'STEM+DroidFiller']['num_internal_activities'], alternative='less')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "WilcoxonResult(statistic=259.5, pvalue=0.12406457752193845)"
      ]
     },
     "execution_count": 134,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import scipy.stats as stats\n",
    "\n",
    "stats.wilcoxon(full_result_df[full_result_df.technique == 'STEM+Context']['num_covered_states'], full_result_df[full_result_df.technique == 'STEM+DroidFiller']['num_covered_states'], alternative='less')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAArsAAAG1CAYAAAD5gTxvAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/SrBM8AAAACXBIWXMAAA9hAAAPYQGoP6dpAABcoElEQVR4nO3deVhUZf8/8PewL4KiIlJq+IAgKrikqLkE5Ja521dLJR9cSk3LXUnLpVJLxAU093zcnso0zeVXT6lZLrlQ7iii4JYspqDIzty/P3COTKDC4eDMObxf1+UlnJk585kPI7y9ue/76IQQAkREREREGmRh6gKIiIiIiMoLwy4RERERaRbDLhERERFpFsMuEREREWkWwy4RERERaRbDLhERERFpFsMuEREREWmWlakLeNb+/PNPCCFgbW1t6lKIiIiohHJzc6HT6dC0aVNTl0IqU+FGdoUQKI/raAghkJOTUy7nVgv2gD0A2AOAPQDYA4A9AJTtQXn9/Cbtq3Aju4YRXT8/P0XPm5GRgZiYGHh5ecHBwUHRc6sFe8AeAOwBwB4A7AHAHgDK9uDMmTMKVUUVTYUb2SUiIiKiioNhl4iIiIg0i2GXiIiIiDSLYZeIiIiINIthl4iIiIg0q8LtxkBERETalp+fj9zcXFOXQeXE2toalpaWJb4/wy4RERFpghACiYmJSE1NNXUpVM6qVKmCmjVrQqfTPfW+DLtERESkCYagW6NGDTg4OJQoCJG6CCGQkZGB5ORkAIC7u/tTH8OwS0RERKqXn58vBd1q1aqZuhwqR/b29gCA5ORk1KhR46lTGrhAjYiIiFTPMEe3ol6trqIxfJ1LMjebYZeIiIg0g1MXKobSfJ0ZdomIiIhIsxh2iYiIiGQQQpi6BCoBhl0iIiKiUtq7dy+mTJmi6DlDQkIQEhJS5vMcPXoUPj4+OHr0qAJVqR93YyCSYe/xa/j651jk643/Vy/0euTm5sJ6z23oLCrm/yXZA/YAYA+AitsDB1srvNe/CerVdjF1KeVq3bp1pi7hsRo2bIivv/4aXl5epi7FLDDsEsnw07FruHX7wRPukf/MajFf7AF7ALAHQEXswbXE+5oPu+asUqVKaNKkianLMBsMu0Qy5OfrAQCh3RqgkWd16XhWVhbi4xNQt64H7OzsTFWeSbEH7AHAHgAVtwf2tlao7eZk6jLKVUhICI4dOwYA8PHxwfr16+Hj44OIiAj8/PPPuH//Pnx9fTFu3Di0bt1aelxOTg6WLVuGnTt3IiUlBXXq1MHQoUPRu3dv6T5CCKxatQqbNm3CnTt34Ovri2nTpsHf3x8AEBkZie+//x7Tpk3DggULEB8fj+effx4jR45Er169ABRMY3jrrbewfv16tGzZEgDw+++/IyIiAhcvXsRzzz2HiRMnYt68eejRowfGjBlT7GMMrxUANmzYIB3bsmUL1q1bh6tXr6J69ero27cvRo0aVapL+D5LDLtEMugfLkqoVcMJ3nUejV5kZGQg974NvGpVrrB7PbIH7AHAHgDsgZbNmDEDkyZNkj728vLCwIEDcfv2bYwbNw41atTA1q1bMWzYMKxevVoKvBMnTsSBAwcwcuRING7cGAcOHMDUqVNhbW2Nbt26AQCio6ORk5ODDz/8EHl5eZg3bx5GjhyJAwcOwMqqILalpKRg9uzZGDlyJJ5//nmsWbMGU6ZMgZ+fHzw9PYvUe+7cOQwbNgwBAQFYsmQJrl27hg8++AA5OTmlfu0rVqzAwoULMWjQIISFhSEmJgaRkZG4desW5syZI7el5Yphl0gGw1RdbudIRFTxeHl5oVKlSgCAJk2a4JtvvsGFCxfwzTffoHHjxgCA9u3bIyQkBOHh4di6dStiY2Px448/4oMPPsDgwYMBAK1bt8bNmzdx9OhRKeza2Nhg5cqVqFKlCgDg3r17mD59OuLi4lC/fn0AQGZmJj799FMpRHt4eCAoKAgHDhwoNuyuWLECVatWxfLly2FjYwMAqFy5shTYS+r+/ftYtmwZ+vfvj+nTpwMA2rZtiypVqmD69OkIDQ1FvXr1SnXOZ6HizJgnUpD+Ydq1sGDaJSKq6I4cOQJXV1c0bNgQeXl5yMvLQ35+PoKCgnD27FmkpaUhOjoaANCpUyejx0ZGRuLjjz+WPvfy8pKCLgDUqlULQEHQLKzwnNyaNWsCKPhtQnFOnDiBdu3aSUEXALp27SqNFJfUn3/+iaysLAQHB0uvMy8vD8HBwQCAQ4cOlep8zwpHdolkMIRdXqmHiIhSU1ORkpKChg0bFnt7SkoKUlNTAQDVqlV74rn+OeXF4uFOHnq93ui4vb19kfs8bt/ftLQ0VK1a1eiYlZXVU2v5J8NrePvtt4u9PTk5uVTne1YYdolkMHxDsWTYJSKq8JycnODh4YHw8PBib69VqxacnZ0BAHfu3JFGYgHg8uXLSE1NxYsvvlhu9bm4uOD27dtFjqelpUkfGwZv/hmqHzx4AEdHRwCQXkN4eDg8PDyKnK969epFjpkDTmMgksGwQE3Hf0FERBWSRaG9kwMCAnDr1i1Uq1YNfn5+0p9Dhw5h9erVsLS0lMLsvn37jM4THh6OTz/9tFxrbd26NX799VdkZmZKxw4fPoysrCzpc8Mc5MTEROlYWloaLl++LH3euHFjWFtbIykpyeh1WllZISIiAjdu3CjX1yEXR3aJZDD8x9eCI7tERBWSs7Mz/vzzTxw5cgQdO3bExo0bERoaihEjRsDd3R2HDx/GqlWrMGjQIFhbW6N+/fro0qUL5s+fj6ysLPj6+uLXX3/F/v37ERUVVa61vvvuu9i3bx+GDh2KYcOGITU1FREREUb38fHxgbu7O5YuXYpKlSpBp9NhxYoVRtMlXFxcMGzYMCxevBjp6elo2bIlkpKSsHjxYuh0OmkBnblh2CWSwTCyywVqREQV08CBA3H27FkMHz4cc+fOxaZNm7BgwQLMnz8f9+/fx/PPP48JEyZgyJAh0mPmz5+PqKgo/Oc//8Hdu3fh6emJJUuWoEOHDuVaq4eHBzZt2oS5c+di7NixcHV1xZQpUzBx4kTpPpaWlliyZAnmzJmD8ePHo3r16hg8eDCuXLmC+Ph46X6Gx2/evBmrV69G5cqV0bp1a4wfPx5OTua5vzLDLpEMhjm7HNklIqqYWrVqhf379xsde9o+szY2Nhg/fjzGjx9f7O2FL9xg0LJlS1y8eFH6fMyYMRgzZkyR+xW+zz8fAwD169fHf/7zH6NjhcMuAPj7++Orr7564msACoL+wIEDn3o/c8EZh0QycOsxIiIidWDYJZLh0dZjJi6EiIiInojTGIhkMFxBjdMYiIhIrf451UGrOLJLJAMXqBEREakDwy6RDFygRkREpA4Mu0QycIEaERGROjDsEsnABWpERETqwLBLJIO0QI0ju0RERGaNYZdIBj3n7BIREakCwy6RDELPsEtEROUjODgYPj4+0p9GjRohMDAQM2bMwJ07d8p07m3btsHHx+eJ9/Hx8cG2bdsAAEePHjWq5Z9/Hjx4IN3nxo0bUv2RkZElfr7yZnb77K5YsQIHDx40umTevn37sHTpUly5cgUuLi7o3Lkz3n//fdjZ2ZmwUqrIuPUYERGVpyFDhmDIkCEAgKysLMTGxmL+/PkYNGgQvv76azg5Ock6b9euXdGuXbtSP27Lli1wd3cvctzBwQFNmzbFwYMHUbVqVVk1lTezCrubNm3CokWL0Lx5c+nYiRMnMHr0aLz33nvo0qULrl69io8++gipqamYO3euCauliswwZ5cDu0REVB4cHBzg6uoqfV67dm34+vritddew+rVqzFu3DhZ57Wzs5M1WFi1alWjegqzsbF57G3mwCymMSQlJWHEiBEIDw+Hh4eH0W1fffUVWrZsiREjRsDDwwMvv/wyxo0bh507dyInJ8c0BVOFx63HiIjUQQiBrOw8k/wx7MmulOeeew4dO3bE7t27ARRMN1iyZAmCgoLQtm1bJCQkICsrC4sWLcIrr7wCPz8/9OzZEz/++KN0jn9OK0hMTMTIkSPRtGlTtG/fHjt37ix1Xf+cxvAkOTk5mD9/Ptq1a4emTZuiX79+OHjwoFF9HTt2xCeffIIXX3wRo0aNKnU9/2QWI7vnzp2DtbU1vv/+eyxduhQ3b96UbhsyZAgsLIwzuYWFBXJzc5Genm62Q+akXXn5euljztklIjJfQghMiTqImISyzXOVy9ejKj4b3RY6BX9WeHt7Y8eOHXjw4AEAYPPmzVi1ahXy8/Ph4eGBUaNG4fz585g5cyZeeOEF7Nq1C++//z6ioqLQoUMHo3Pl5eVh2LBhqFSpEjZu3IicnBzMmjVLsVqLExYWhsuXLyM8PBxubm7Yv38/RowYgaioKAQGBgIArl27huTkZGzfvh1ZWVllfk6zCLvBwcEIDg4u9rYGDRoYfZ6bm4t169ahUaNGsoOuEAIZGRmyHvs4mZmZRn9XRBWhB0fPJSHy27PS59lZWciwyJc+rwg9eBr2gD0A2AOAPQCU7YEQQtHQqFbOzs4AgPT0dABAz5494efnBwC4fPky9u7di+XLl0vBccyYMbhw4QKWL19eJOweOXIEly5dwk8//YQ6deoAAObOnYtevXoVed5u3boV6f+qVauMpp4+zdWrV7Fr1y5s374dvr6+AIDQ0FBcuHABa9askWoGgFGjRqF27dolPveTmEXYLam8vDxMnjwZly5dwqZNm2SfJzc3FzExMQpW9khCQkK5nFdNtNyDX6PvIjevYGTXvao1riZcKnZ0V8s9KCn2gD0A2AOAPQCU64GNjU2p7q/T6fDZ6LbIzsl/+p3Lga2NpeIB/f79+wCASpUqAQBeeOEF6baLFy8CAF588UWjx7Ro0QIRERFFzhUbG4vKlStLQRcAfH19i53Tu3LlSri5uRkd++fnT3P+/HkAwIABA4yO5+bmSiHe4J/TWstCNWE3PT0dY8eOxbFjxxAVFQV/f3/Z57K2toaXl5eC1RX8rzUhIQEeHh6wt7dX9NxqURF68FvseQAP0Lt9XfR7xbPInN2K0IOnYQ/YA4A9ANgDQNkexMXFyXqcTqeDna1q4s5TnTt3Dh4eHnB0dASAEi02E0LAyqpoD3Q6HfR6fZHjxd33ueeeQ61atWRUbFwHULAhgaF+g39OWVVyxy1VfPWTk5MxfPhw3Lx5E2vWrEGLFi3KdD6dTgcHBweFqjNmb29fbudWCy33wNKy4J+Mo6MtKlVyfOz9tNyDkmIP2AOAPQDYA0CZHnAKQ8Fisr1792L48OHF3m5YeBYdHY2goCDp+IkTJ4od5PP19cX9+/dx6dIl1KtXD0DBKLxhioTSDM+RkpJiNE114cKFsLCwwPvvv18uz2sWuzE8SVpaGgYPHow7d+5g06ZNZQ66RGWh58UkiIjoGcjIyEBKSgpSUlJw/fp1/Pzzzxg2bBhq1aqF0NDQYh/j6emJoKAgzJo1C7/88gvi4+MRFRWFvXv3Snv2FtayZUs0btwYkydPxsmTJ3HmzBlMnjy5yCirUurVq4egoCDMmDED+/btw/Xr17Fq1SqsWLHCaCqF0sx+ZHfu3Lm4fv06Vq9ejapVqyIlJUW6rWrVqrC0tDRhdVTR8DLBRET0LKxduxZr164FUDD90t3dHV27dsWQIUOKTAEoLCIiAhEREZg2bRru3bsHb29vREZGomPHjkXua2FhgRUrVuCTTz7BkCFDYGdnh3feecdoVyylLVy4EAsXLsRHH32EtLQ01KlTB59++il69+5dbs+pE0pvAldGU6dOxc2bN7Fhwwbk5+ejadOmyM7OLva+e/fuLfX8kTNnzgCAtHJRKRkZGYiJiYGvr2+F/XVVRejBgs3R+CX6BoZ0b4jegUV/JVQRevA07AF7ALAHAHsAKNuDp/38zsrKQnx8POrWrcsrrFYApfl6m93I7rx586SPLS0tcfr0aRNWQ2RMPJzHz7ljRERE6mD2c3aJzIk0jYH/coiIiFSBP7KJSoFzdomIiNSFYZeoFKTdGCwYdomIiNSAYZeoFARHdomIiFSFYZeoFPRcoEZERKQqDLtEpWCYs2vJfzlERESqwB/ZRKVgCLsc2SUiIlIHhl2iUuACNSIiInVh2CUqBcGRXSIiIlVh2CUqBcMCNUuGXSIiKkd5eXn4z3/+gz59+qBp06Zo1aoVhgwZgt9//13R5/nrr7+we/duxc6XkZGBTZs2KXY+JTDsEpXCoyuoMewSEVH5yM7OxltvvYV169YhJCQE3333HdatWwdPT0+EhoZi586dij3XlClT8Ntvvyl2vrVr12LNmjWKnU8JVqYugEhNDHN2ObBLRETlZfHixbh48SJ27doFd3d36fi0adOQnp6OTz75BMHBwXB0dDRhlcUzTPczJwy7RKUgOLJLRKQqQgiI3GyTPLfO2rbUazxyc3OxdetW9OnTxyjoGowdOxZvvvkm7OzskJqaisWLF2Pfvn24e/cuGjRogHHjxqFly5YAgMjISERHR+Oll17Cxo0bcffuXTRu3BizZs2Cp6cnQkJCcOzYMQDAsWPHsG/fPuTk5GDx4sX4/vvvkZ6ejnr16uG9995D27ZtAQAjRozA+fPnsWfPHlSqVAnJycno3r07unXrhipVqiAqKgoA4OPjg71796JWrVplaaEiGHaJSkHPK6gREamGEAJ/rZ+G7BsXTfL8trXq47m3PilV4L1+/TpSU1PRrFmzYm93c3ODm5sb8vPzMWTIEOTm5mL+/PmoWrUq1q9fj6FDh2Lz5s3w9/cHAJw4cQK2trZYuXIlcnNzMXnyZMyaNQvr169HZGQkRowYgZo1a+Kjjz4CAISFheHy5csIDw+Hm5sb9u/fjxEjRiAqKgqBgYH45JNP0L17d3z++eeYNWsWwsLC4ObmhilTpiA3NxcZGRnYs2cPvv32W1StWrXsTVQAwy5RKTycxcCRXSIi1VDX9+u0tDQAQOXKlZ94v4MHD+LcuXPYuXMnvL29AQCzZs3CmTNnsGbNGixevBhAwUK3zz//XDrfG2+8gfnz5wMAqlSpAmtra9jZ2aFq1aq4evUqdu3ahe3bt8PX1xcAEBoaigsXLmDNmjUIDAxE9erV8fHHH2P06NHIzc1FdHQ0tm7dChsbG9jY2MDBwQGWlpZwdXUtl/7IwbBLVArSPrsc2SUiMns6nQ7PvfWJqqYxGEZDU1NTn3i/2NhYODk5SUEXKHi9zZs3x8GDB6Vj1atXNwrOTk5OyM3NLfac58+fBwAMGDDA6Hhubi6cnZ2lzzt06ICePXti27Zt+OCDD+Dp6VmyF2ciDLtEpfBon10TF0JERCWi0+mgs7EzdRklVrt2bVSvXh1//PEHunbtWuT2y5cv49NPP33sNAchBKysHsU7GxubEj+34Wfcpk2biix+s7B4tIFXbm4uLl68CCsrKxw6dAiDBw8u8XOYArceIyqhv9MykZWTD4DTGIiIqHxYWFjg9ddfx7Zt23Dr1q0it69evRpnzpxBo0aNcP/+fcTGxkq3CSEQHR0NLy8vWc9dr149AEBKSgpeeOEF6c+2bduwbds26X5LlixBYmIivvzySxw5cgRfffWVdJs5XnSJYZeoBM5d+RuhH/8Pt24/AMCwS0RE5WfEiBHw8PDAgAEDsH37dly7dg2nT59GWFgYtm/fjo8//hjt2rWDr68vJkyYgGPHjuHy5cuYPXs2YmNjSzXS6ujoiJs3byIxMRH16tVDUFAQZsyYgX379uH69etYtWoVVqxYgTp16gAAoqOjsXr1anz44YcICAjAqFGj8Nlnn+Hq1asAAAcHB6SlpSE+Pv6x0yWeNYZdohK4lnQfQgDWVhbw9agKr1pVTF0SERFplL29PTZu3Ii+ffti1apV6NmzJ9555x0kJydjw4YN6NKlCywtLbF27Vo0aNAAo0ePRt++fXHp0iWsW7cOTZo0KfFzvfHGG4iNjUWPHj2Qn5+PhQsXolOnTvjoo4/QtWtXbN++HZ9++il69+6NBw8eYMqUKQgKCsJrr70GABg+fDheeOEFTJ48Gfn5+ejUqRNcXV3Ro0cPaQ6wqemEOe7+W47OnDkDAPDz81P0vBkZGYiJiYGvry8cHBwUPbdaaLkHuw/FY/m202jj/xymDm7x2PtpuQclxR6wBwB7ALAHgLI9eNrP76ysLMTHx6Nu3bqws1PPHF2SpzRfb47sEpUAr5xGRESkTgy7RCXAK6cRERGpE8MuUQnwymlERETqxLBLVAJ6fcHfHNklIiJSF4ZdohLgyC4REZE6MewSlQAXqBERqUMF22SqwirN15lhl6gEuECNiMi8WVtbAyjY7oy0z/B1Nnzdn8TqqfcgImlkl9MYiIjMk6WlJapUqYLk5GQABVfyMsdL11LZCCGQkZGB5ORkVKlSBZaWlk99DMMuUQk8zLoc2SUiMmM1a9YEACnwknZVqVJF+no/DcMuUQnoOY2BiMjs6XQ6uLu7o0aNGsjNzTV1OVROrK2tSzSia8CwS1QChjm7/I0YEZH5s7S0LFUYIm3jAjWiEuCcXSIiInVi2CUqgXyGXSIiIlVi2CUqAcEFakRERKrEsEtUAnrO2SUiIlIlhl2iEhB67sZARESkRgy7RCWQ/3Bk15JDu0RERKrCsEtUAoY5uzqO7BIREakKwy5RCXDrMSIiInUyu7C7YsUKhISEGB2LiYnBoEGD0KRJEwQHB2P9+vUmqo4qKkPYZdYlIiJSF7MKu5s2bcKiRYuMjt29exehoaGoU6cOtm7dinfffRfh4eHYunWraYqkCsmwG4MlpzEQERGpillcLjgpKQkzZszA0aNH4eHhYXTbN998A2tra8yePRtWVlbw9PTE1atXsXLlSvTt29c0BVOF82jrMYZdIiIiNTGLsHvu3DlYW1vj+++/x9KlS3Hz5k3pthMnTiAgIABWVo9KbdWqFVasWIHbt2+jevXqpiiZNOrqrXu4lnS/yPGkvzMAcOsxIiIitTGLsBscHIzg4OBib0tMTIS3t7fRsRo1agAAbt26JSvsCiGQkZFR+kKfIDMz0+jvikjtPbj3IAfvR/wqXRq4OEKf98T3jtp7oAT2gD0A2AOAPQCU7YEQgr9dI1nMIuw+SVZWFmxsbIyO2draAgCys7NlnTM3NxcxMTFlrq04CQkJ5XJeNVFrD5LTcpGvF7DQAbVdbYrc7mBriSpWaYiJSX/qudTaAyWxB+wBwB4A7AGgXA/+mQeISsLsw66dnR1ycnKMjhlCroODg6xzWltbw8vLq8y1FZaZmYmEhAR4eHjA3t5e0XOrhdp74JiUDiAJlRys8fmYl2WdQ+09UAJ7wB4A7AHAHgDK9iAuLk6hqqiiMfuwW7NmTSQnJxsdM3zu5uYm65w6nU52UH4ae3v7cju3Wqi1B7a2uQAASwuLMtev1h4oiT1gDwD2AGAPAGV6wCkMJJdZbT1WnBYtWiA6Ohr5+fnSsd9//x1169ZFtWrVTFgZaU2+njsuEBERaY3Zh92+ffsiPT0d06ZNQ1xcHLZt24Z169bhnXfeMXVppDHi4fZi3HGBiIhIO8w+7FarVg2rV69GfHw8evfujaioKEyePBm9e/c2dWmkMY8uCWziQoiIiEgxZjdnd968eUWO+fv74+uvvzZBNVSRPBzY5cguERGRhsgOu+np6Xjw4AHc3NyQm5uLDRs24K+//kLnzp3RokULJWskeibypZFdhl0iIiKtkDWN4dSpUwgKCsLGjRsBAJ988gk+//xzfP/99xg8eDD27t2raJFEzwIvCUxERKQ9ssLuokWL4OnpiX79+iEzMxM7duzAgAEDcOzYMbz++utYvny50nUSlTsuUCMiItIe2SO7I0eORO3atXHo0CFkZ2ejZ8+eAICuXbvi0qVLihZJ9CxwgRoREZH2yAq7FhYW0iV7f/vtNzg7O8Pf3x9AwVxeOzs75Sokekb0XKBGRESkObIWqDVq1AhbtmyBnZ0dfvjhBwQGBkKn0+Hvv//GqlWr0KhRI6XrJCp30sguwy4REZFmyBrZnTRpEg4fPow33ngDlpaWGDlyJACgW7duSEhIwNixY5WskeiZ4AI1IiIi7ZE1stuwYUP89NNPuHz5MurVqydd73rmzJlo1qwZXF1dFS2S6FkQD0d2LRl2iYiINEP2FdQqVaoEPz8/XLt2Db/++ivS09PRsmVLBl1SrUcjuyYuhIiIiBQj+6ISO3bswIIFC5CcnAwLCwts2bIFkZGRsLa2xoIFC2BjY6NknUTljgvUiIiItEfWyO6ePXswZcoUtGrVCgsXLoRerwcAdOzYEQcOHMCyZcsULZLoWTAsUOOcXSIiIu2QNbK7fPlyvPHGG5g5cyby8/Ol43379sWdO3fwzTffcJEaqY4h7FpyZJeIiEgzZI3sxsfHo2PHjsXe1rhxYyQlJZWpKCJTkK6gxpFdIiIizZAVdqtVq4bLly8Xe9vly5dRrVq1MhVFZApcoEZERKQ9ssJu165dsWTJEvzwww/IyckBUDDP8ezZs1i2bBm6dOmiaJFEz8LDqedcoEZERKQhsubsjh07FrGxsRg7diwsLAryckhICDIyMtC8eXO8//77ihZJ9CzwohJERETaIyvs2tjYYPXq1Th06BCOHDmCtLQ0ODk5ISAgAC+//DLDAqkSF6gRERFpj+x9dgGgTZs2aNOmjVK1kMbkZ9zD/dO/QORmm7qUEhFnb6GTXRpqp1/B3d+uyTpHbm4u7FJSkJ52EdnW1gpXqA7sAXsAsAdAxe2Bha09nPyDYGHnaOpSiACUIuyGhYVh1KhRqF27NsLCwp54X51Ohzlz5pS5OFK31N93IO3IdlOXUWI+AHwcANwH7v4q/zz2ANLjFCpKpdgD9gBgD4AK3AOdBSq36GrqKogAlCLsHj16FIMHD5Y+JnoafWY6AMDW3Qs2Nf9l4mqe7qdjV5GfL/Bi/RpwdXGQdY68vDykpt5FlSousLIq0y9OVIs9YA8A9gCouD2wsLWHo29rU5dBJCnxv759+/YV+zHR44iH2xs41m+JKi/1MXE1T7ftt13IzslHxy4d4FpN3q/fMjIy8FdMDF7w9YWDg7zArHbsAXsAsAcAe0BkLmRtPRYWFobr168Xe9uVK1cwYsSIMhVFWvFwLy+drLfZMyf0vKgEERGR1pR4ZPevv/6SPv7uu+/QoUMHWFpaFrnfr7/+isOHDytTHambXl1hl1uPERERaU+Jw+6sWbPw668Fq3Z0Oh1Gjx5d7P2EENyhgQAAQhjCrjrC48OBXVioI5sTERFRCZQ47M6ePRuHDx+GEAIffPABRo4ciTp16hjdx8LCAs7OzmjZsqXihZIKGUZKVZIeDfvs8gpqRERE2lHisOvm5obevXsDKBjZDQwMhIuLS7kVRhpgmMYA8w+PhqALcM4uERGRlpQ47B4/fhwNGjSAo6MjatWqhbi4J28c2KJFizIXR+pmmMaghpFdIQqFXY7sEhERaUaJw25ISAi++eYb+Pv7IyQkBDqdziggAJCO6XQ6xMTEKF4sqYxQzwI1faH3MheoERERaUeJw+769evh6ekpfUz0VCrajaHQLAZwYJeIiEg7Shx2AwICpI+dnZ1Rv379cimItEOoaIGa0Zxdpl0iIiLNkJVCevXqhe7du2PNmjVISkpSuibSChVtPWY0Z1cF9RIREVHJyAq7UVFR8PT0RGRkJIKDgxEaGort27cjIyND6fpIzQwBUg3TGDiyS0REpEmyUkiHDh2waNEiHD58GHPnzoWtrS2mT5+ONm3aYNKkSfjtt9+UrpNUSNqNQQ1ht9CcXS5QIyIi0o4Sz9ktjoODA3r06IEePXogNTUVUVFR+O9//4tdu3ZxNwZ6tEBNbXN2mXWJiIg0o0xhFwDOnj2L3bt344cffsCtW7fg6+uLnj17KlEbqZ0Ktx6z0HFkl4iISEtkhd24uDjs3r0be/bswbVr11CjRg10794dPXv2RL169ZSukVTq0TQG8w+P0s4RKqiViIiISk5W2O3WrRscHBzQuXNnzJw5E61atWJIoKJUtEAt/+E0Bi5OIyIi0hZZYTc8PBwdOnSAnZ2d0vWQlujVtPVYwd/8TxsREZG2lDjs/vXXX3B1dYW1tTWaNWuGO3fuPPH+zz33XJmLI3WTpjGoaIGapfmXSkRERKVQ4rD7yiuv4Ouvv4a/vz+Cg4OfOgLG3RhITdMYOGeXiIhIm0ocdufMmYPatWtLHz/LUJCXl4elS5di+/btSE1NRYMGDTBp0iQ0adLkmdVAMoj8gr9VEHalObsMu0RERJpS4rDbu3dv6eNWrVpJUxr+KTs7G+fOnVOmuoe++OILbNmyBfPmzUPt2rWxatUqDBs2DHv27EGNGjUUfS5SjjRaqoJpDIZauUCNiIhIW2SlkFdeeeWx0xROnz6N0NDQMhX1Tz///DO6deuGtm3b4oUXXsDUqVNx//59nDx5UtHnIYWpaIGa4ZoSHNklIiLSlhKP7H722WdITU0FUDAKtmzZMri4uBS5X0xMDJycnBQrEACqVauG/fv3Y9CgQXB3d8fXX38NGxsb1K9fX9b5hBDIyMhQtMbMzEyjvyuiwj3I+/smcv++CQDIzs6FULjfSku8nQYA0OnK9t7g+4A9ANgDgD0A2ANA2R4IIbiugmTRCcPvb59iy5Yt+OKLLwAAt27dQrVq1WBjY2N0H0tLSzg5OWHo0KF47bXXFCvy8uXLeP/993Hp0iVYWlrCwsICkZGRCAoKKvW5zpw5g5ycHMVqo+I5nN0D2xsnAQBpbd+GvlJ10xb0FL+evYd9p+8BAGYOqGXiaoiIqDg2Njbw8/MzdRmkMiUe2f2///s//N///R8AIDg4GMuWLZM9slpacXFxcHJywtKlS+Hm5oYtW7Zg4sSJ2LhxI3x9fUt9Pmtra3h5eSlaY2ZmJhISEuDh4QF7e3tFz60WhXuQHW+PLAA2tRvAp0U7U5f2VBdT4gHcQ73alWW9pwz4PmAPAPYAYA8A9gBQtgdxcXEKVUUVjayLSuzbtw/Xrl3Dt99+i9dffx1Awejr1q1bMWjQIEX32L116xYmTJiAdevWoXnz5gAAPz8/xMXFITIyEsuWLSv1OXU6HRwcHBSrsTB7e/tyO7da2NvbI+/hhrVOvq1V0Q8rq4LFlh7ulRWpl+8D9gBgDwD2AGAPAGV6wCkMJJesBWonT55Er169sGbNGunYvXv38P3336N3796IjY1VrMBTp04hNze3yK8tGjdujKtXryr2PKQwFS1OAwA9d2MgIiLSJFlhd8GCBWjWrBm+++476VjTpk2xd+9e+Pv74/PPP1eswJo1awIALl68aHQ8NjYWHh4eij0PKUu6epoK9tgFAMF9domIiDRJVhI5d+4chg4dCjs7O6Pjtra2GDx4ME6dOqVIcQDg7++PF198EVOmTMHvv/+OhIQELFq0CEeOHMHbb7+t2POQwoS6RnbzpSuombgQIiIiUpSsObt2dnZISkoq9ra7d+/CQsGLCFhYWOCLL77AokWLEBYWhrS0NHh7e2PdunVo3LixYs9DCjNMY1DBBSUAQK/nNAYiIiItkhV227VrhyVLlsDX1xc+Pj7S8cuXLyMyMhLt27dXrEAAqFy5MmbMmIEZM2Yoel4qP9LV09QyjcFwUQmGXSIiIk2RFXYnTpyIN954A71790atWrVQtWpV3L17F9evX0etWrUwefJkpesktZGmMagj7Oo5Z5eIiEiTZIVdV1dX7Ny5E9u2bcMff/yB1NRUuLm5YdCgQejTpw8cHR2VrpPU5tFQqWnrKCFpNwaGXSIiIk2RFXYBwMHBAYMGDcKgQYOUrIc04tFuDOoIj3ouUCMiItIk2WH39OnTOHr0KHJycqT5mUIIZGRkIDo6Gt98841iRZIK6dU1jYFzdomIiLRJVtjdtGkTPvnkEynkFmZhYYG2bduWuTBSObXO2WXYJSIi0hRZSWTjxo1o3749jh49iiFDhqBfv344efIkFi9eDFtbW/To0UPpOkll1HZRCS5QIyIi0iZZSeTGjRsYMGAAKleujEaNGiE6Ohp2dnbo3Lkz3n77baxfv17pOkltDKP+KgmPvFwwERGRNskKu9bW1tLV01544QVcvXoVubm5AIAXX3wRCQkJihVIKqXSi0qoJJsTERFRCclKIr6+vti/fz8AoG7dutDr9dIlghMTE5WrjlRLtReVYNolIiLSFFkL1EJDQzF69Gjcu3cPc+bMwSuvvILJkyejU6dO2LlzJ1588UWl6yS1kRaoqSM8GqYxWHIaAxERkabIGnbr0KEDli9fDk9PTwDA7Nmz4eHhga+++gr/+te/8NFHHylaJKmQyC/4Wy3TGKSRaIZdIiIiLZG9z25gYCACAwMBAC4uLli7dm2R+wghsHTpUvTv3x+urq6yiyT1Uds0Bm49RkREpE3lmkT0ej2WLl2K5OTk8nwaMkcqu6gEF6gRERFpU7knkeIuPEEVgMq2HjOUa6mSeomIiKhk1DHsRqojXVRCbXN2OY2BiIhIU9SRREh9VDqNgVuPERERaYs6kgipj1BZ2OUV1IiIiDRJHUmEVEeaxqCSsPvoohKmrYOIiIiUpY4kQuqjsgVq3HqMiIhImxh2qXyobYGanheVICIi0iJ1JBFSHaG2kV3BBWpERERaJPsKaiVhaWmJvXv3okaNGuX5NGSO1LYbAxeoERERaVKJw25wcHCpfsW7d+9eAMDzzz9f+qpI9dS2z+6jBWoMu0RERFpS4rAbEBAghV29Xo/du3fDyckJL7/8MlxdXZGamopDhw7hzp076N+/f7kVTCqhtq3HpAVqJi6EiIiIFFXisDtv3jzp4/DwcPj7+2PNmjWwt7eXjufm5mLkyJHIyMhQtkpSH5VOY+ACNSIiIm2RlUS2bNmC4cOHGwVdALC2tkZISAj27NmjSHGkYioLj9x6jIiISJtkD7ulpaUVe/yvv/6Cra2t7IJIG4TapjFwNwYiIiJNkpVEgoODER4ejkOHDknHhBD46aefsGjRInTt2lWxAkmlVDaNwZDNGXaJiIi0RdbWY2FhYYiLi8PQoUNhY2ODypUr4+7du8jPz0ebNm0wadIkpeskFSnYY/fhNAaVrPh6tPWYiQshIiIiRckKu87Ozvjmm29w4MABnDhxAvfu3YOLiwtatWqF1q1bK10jqY1hHy9ANSO7XKBGRESkTbIvKqHT6RAYGIjAwEBkZ2fD2toaFhwWI+DRnABAPVdQ4wI1IiIiTZKdTq9cuYKxY8ciICAATZs2RUxMDGbNmoUNGzYoWR+pUaGwq5ZpDIIL1IiIiDRJVhKJiYnB66+/jnPnzqFbt25SULC0tMScOXPw3XffKVokqYtQ5chuwd8Mu0RERNoiaxrDZ599hkaNGmHt2rUAgM2bNwMApk+fjuzsbKxfvx69e/dWrkpSFxXO2c3nAjUiIiJNkvWj/eTJk/j3v/8NKyurIgt6unbtioSEBCVqI7XSq3caAxeoERERaYusJGJra4usrKxib0tNTYWNjU2ZiiK1U9/ILheoERERaZOsJNKmTRssWbIEiYmJ0jGdTocHDx5g7dq1eOmllxQrkFRIX3jOrjrCLheoERERaZOsObuTJk1C//790aVLF9SvXx86nQ7z5s1DfHw8hBCIiIhQuk5SEVFozq5apgVIC9Q4sktERKQpsobd3N3dsWPHDgwePBhCCNSpUwcZGRno1q0btm3bhtq1aytdJ6mJUNelgoFCV1Bj1iUiItIUWSO7y5YtQ+fOnTFu3Dil63ms7du3Y+XKlbh+/Trq1KmD0aNH49VXX31mz0+loMawq+cCNSIiIi2SlUZWrFiBGzduKF3LY+3YsQPTpk3DwIEDsXv3bnTr1g3jx4/Hn3/++cxqoFIw7Gygkp0YgEcju5Yc2iUiItIUWWnEy8sL8fHxStdSLCEEFi9ejLfeegsDBw5EnTp1MHLkSLz00ks4duzYM6mBSkfo1Teyy63HiIiItEnWNIagoCBERETgt99+g4+PDxwcHIxu1+l0ePfddxUpMD4+Hjdv3kT37t2Njq9Zs0aR81N5eLhATUXBMZ8L1IiIiDRJVtiNiooCABw6dAiHDh0qcrvSYRcAMjIyMHToUJw/fx61atXCyJEjERwcLOucQghkZGQoUp9BZmam0d8Vxf1DW5Bx8n+AAAQEqugFbhvyok6neJ/Lw49HryMnNx8AkJ2dhbKUXFHfB4WxB+wBwB4A7AGgbA+EEPztG8miE4X3iTJDO3bswOTJk1GrVi2MHj0a9evXx48//ojly5fjyy+/ROvWrUt1vjNnziAnJ6ecqq14nH+JgmXWvWJvy63mgfQWA55xRaW39qdkXEspeE9M7/88rCz5zZSIyBzZ2NjAz8/P1GWQysga2S3s/v37SE5ORu3atWFpaQlLS0sl6pJYW1sDAIYOHYrevXsDAHx9fXH+/HlZYddwTi8vL0XrzMzMREJCAjw8PGBvb6/ouc1Z8kEr6AFU6TEO+ZWq48aNG6hVqxZsbe1g6VxdFYvU7A+mA8jBe//XCH6N3Mt0ror6PiiMPWAPAPYAYA8AZXsQFxenUFVU0cgOu0ePHkV4eDjOnj0LnU6HLVu2YNWqVahZsyamTp2qWIFubm4AAG9vb6PjXl5e+OWXX2SdU6fTFZlnrBR7e/tyO7c50j2cn+vo+jzynd2gv/MAjm511NWDh78Wc6rkoFjdFe19UBz2gD0A2AOAPQCU6QGnMJBcsobdjhw5gqFDh8LOzg4TJ06UVrLXr18f69evx5dffqlYgQ0bNoSjoyNOnTpldDw2NhZ16tRR7HlIJmlPXfV+EzLsscvFaURERNoja2R30aJFeOWVV7B48WLk5eVh/vz5AIARI0YgIyMDW7ZsQWhoqCIF2tnZYdiwYVi6dCnc3Nzg7++P3bt349ChQ1i3bp0iz0HyCRXuqftPQrp6GsMuERGR1sgKuzExMdJuC//8tUKbNm3wn//8p+yVFTJq1CjY29tj4cKFSEpKgqenJyIjI9GyZUtFn4dkUOGeuv9keAkMu0RERNojK+w6OTkhJSWl2Ntu3boFJyenMhVVnNDQUMVGi0lBKrw08D8Zrp6m4sFpIiIiegxZP95feeUVLFy4EGfOnJGO6XQ6JCYmYvny5QgMDFSqPjJz4mHYVfM0Bj2vnkZERKRZskZ2J0yYgFOnTqFfv36oXr06AGD8+PFITEyEu7s7xo8fr2iRZMb0XKBGRERE5ktW2K1cuTK2bNmC7du34/fff0dqaiqcnJwQEhKCPn36VNj9BCskaVRUvSO7XKBGRESkXbLC7oULF1C/fn3069cP/fr1U7omUhGhhTm7XKBGRESkWbISSq9evdC9e3esWbMGycnJStdEamK42rSawy4XqBEREWmWrB/vUVFR0vZfQUFBCA0Nxfbt25GRkaF0fWTGhBDSbgxcoEZERETmSFZC6dChAxYtWoTDhw9j7ty5sLW1xfTp09GmTRtMmjQJv/32m9J1kjkyTGEAuECNiIiIzJKsObsGDg4O6NGjB3r06IHU1FRERUXhv//9L3bt2oWYmBilaiRzZZjCABRMYxCPv6s5MyxQs2TYJSIi0pwyhV0AOHv2LHbv3o0ffvgBt27dgq+vL3r27KlEbWTmRKGRXZ1Op9qw+2j3NIZdIiIirZEVduPi4rB7927s2bMH165dQ40aNdC9e3f07NkT9erVU7pGMleFR3YtLAC9OtOutECNWZeIiEhzZIXdbt26wcHBAZ07d8bMmTPRqlUrjopVRPrCc3YtAOSbrJSyMMzZ5XuYiIhIe2SF3fDwcHTo0AF2dnZK10MqYjyNQcVhl3N2iYiINEv2yC4A/Prrrzh27Bju3bsHFxcXNG/eHO3atVO0QDJjhXdjUPHWY4JbjxEREWmWrLCbk5ODUaNG4eDBg7C0tISLiwvu3r2LlStXolWrVlixYgVsbGyUrpXMjV4bW4/lG66gxpFdIiIizZE1HBcZGYno6Gh8/vnnOH36NA4ePIhTp05h7ty5OHnyJL744gul6yQzJAotUNOp+ApqQlqgxrBLRESkNbISyq5duzB69Gj06NEDlpaWAAArKyv06tULo0ePxs6dOxUtksyUYRqDioMuUPiiEiYuhIiIiBQn68f7nTt30KBBg2Jva9CgAZKSkspUFKmEVsIuR3aJiIg0S1ZKqVOnDqKjo4u97fjx43B3dy9TUaQOht0Y1LywSwghbRes5tdBRERExZO1QO2NN97AvHnzYGdnh9deew3Vq1fH7du3sWvXLqxatQqjR49Wuk4yQ/eO/7+CD1QcElNSM6WPuUCNiIhIe2SF3TfffBPnz59HeHg4FixYIB0XQqB37954++23FSuQzFfevdsAAFF4VwaVuZ50X/rYycHahJUQERFReZAVdi0sLPDpp59iyJAhOHbsGNLS0lC5cmUEBATA09NT6RrJXD2cxlCt479NW0cZGBanedWqzGkMREREGiQr7AJAdHQ0fv/9d7z77rsAgPPnz2PJkiUYPnw4GjVqpFiBZL4eXYxBvQvUDPN1OYWBiIhIm2SllAMHDmDw4ME4ePCgdEyn0yEhIQEDBgzAiRMnFCuQzJhh+oKKR0Tz9bx6GhERkZbJvqjEa6+9hs2bN0vHfH19sWPHDrz66quIiIhQrEAyY0K69Jhp6ygDXlCCiIhI22SllMuXL6NXr17Fjob16tULFy5cKHNhZP4ebT2m3rAr7bHLaQxERESaJCulODk5IT4+vtjbrl+/DgcHhzIVRSohbVCr3rArDU5zZJeIiEiTZKWUjh07YvHixdi/f7/R8d9++w2LFy9Gx44dFSmOzJwGpjHkC14qmIiISMtk7cYwbtw4nDlzBiNHjoS1tTWqVKmC1NRU5OXloXHjxpgwYYLSdZIZMuyvq+bFXXouUCMiItI0WWG3UqVK+Oqrr3DgwAH88ccfSE1NhZOTE5o3b47AwEBYcJisYtDCNAbO2SUiItI02fvsWlhYICgoCEFBQY+9j16vR8eOHbF8+XLUq1dP7lORudLANAbDyC7n7BIREWlTuaYUIQRu3ryJnJyc8nwaMhFpN4byfRuVK73hohIMu0RERJqk3pRCpqfXwMguF6gRERFpGn/Ek3zSnF31joo+uuSxel8DERERPR7DLsmmiYtK6LlAjYiISMvUm1LI9AwjuyqeA2CYxmDJkV0iIiJNUm9KIdMT+QV/qzgoGqYdcxoDERGRNjHskmyP5ruq920kuECNiIhI0/gjnuSThkXV+zbiFdSIiIi0rVxTik6nQ4sWLeDo6FieT0OmYhjZVfGwqDRnlwvUiIiINEn2FdSSkpJw9uxZ3L9/v9jbe/XqBQsLC2zYsEF2cWTeDLsxqHrOLrceIyIi0jRZYXfPnj2YOnXqY6+MptPp0KtXr7LU9Vjx8fHo06cPPvzwQ/Tp06dcnoNKSBPTGAr+5tZjRERE2iQr7C5atAj+/v4ICwtDlSpVFC7p8XJzczFx4kRkZGQ8s+ekJ9DAPrvSAjVmXSIiIk2SFXaTk5Mxe/ZsNGzYUOl6nigyMhKVKlV6ps9Jj/doGoN6w650UQlOYyAiItIkWWG3SZMmuHDhAlq1aqV0PY91/PhxfP3119i+fTsCAwOf2fOWl5sp6bidmgno82H5dzygzzN1SaVmn50NHYDYG2nQp6cgOzsbVxOzkG97B7a2D0xdXokk/l3wWwJOYyAiItImWWF3xowZGDFiBNLT0+Hn5wcHB4ci92nRokWZizO4d+8eJk+ejOnTp8Pd3b3M5xNCKD4VIjMz0+jvJ7melI6JUUcAAH0cjuFluwuK1vKsLdlyGon51woduW2yWuTS6/MVeU+U5n2gVewBewCwBwB7ACjbAyEEFxOTLLLCbkJCAm7fvo2oqCgAxivZDW/GmJgYZSoEMHPmTDRt2hTdu3dX5Hy5ubmK1ldYQkLCU+9z8UbBP3orS+C5hyOg94UDMmFbLjWVpxRRBaJSVdRQ8ZbNNlYWeM4pU9H3REneB1rHHrAHAHsAsAeAcj2wsbFR5DxUscgKu5999hnq1KmD4cOHo3r16krXZGT79u04ceIEdu7cqdg5ra2t4eXlpdj5gIL/tSYkJMDDwwP29vZPvG86kgH8jbrPVUZDVxfkJFzH850HwqFhe0VrelZeefh3aXqgVewBewCwBwB7ALAHgLI9iIuLU6gqqmhkhd2//voLy5cvx0svvaR0PUVs3boVf//9d5F5ujNmzMCePXuwevXqUp9Tp9MVO/VCCfb29k89t7V1wf9MrSwtpYsZ2NrZlVtNz1pJeqB17AF7ALAHAHsAsAeAMj3gFAaSS1bY9fb2xq1bt5SupVjh4eHIysoyOtapUye899576NGjxzOpQWkPd7sqWBRl+ETFOxoQERERmStZYTcsLAwTJ05Efn4+mjRpUux2YM8991yZiwMANze3Yo9Xq1btsbeZu8LbXQm9+veqJSIiIjJXssJuaGgo8vLy8NFHHz321wrltQBMC/KlS9RCujCDmi+5S0RERGSuZIXdmTNnmnTuzMWLF0323EqQrtpVeBqDBUd2iYiIiJQmK+z26dNH6ToqlGKnMah46y4iIiIicyUr7B4/fvyp91HyohJaYzyy+3AaA0d2iYiIiBQnK+yGhIRAp9NJoQ0ouiUI5+w+Xr4h3+oehV0uUCMiIiJSnqywu379+iLHMjIycOLECezYsQORkZFlLkzLRKEFatJ/GLhAjYiIiEhxssJuQEBAsccDAwPh4OCAL774AitWrChTYVqmLzyNIZfTGIiIiIjKi+IJq3nz5jh27JjSp9UUowVq3HqMiIiIqNwoHnb37dsHR0dHpU+rKfpiFqhxzi4RERGR8mRNY3jrrbeKHNPr9UhMTMTNmzcxfPjwMhemZfrCg7nSyC7DLhEREZHSZIXdwrswGFhYWMDb2xvvvPMO+vbtW+bCtKy4i0roOGeXiIiISHGywu6GDRsAAGlpacjMzITeMFT5UGJiIp577rmyV6dRxV1UgiO7RERERMqTFXavXbuGyZMn49SpU4+9D/fZfTxpzm6hfXa5QI2IiIhIebLC7uzZs5GQkIDRo0ejZs2asOCv4Eul8AK1R3vusodERERESpN9ueBPP/0U3bp1U7qeCsFogRqnMRARERGVG1kJq1KlSqhcubLStVQYopitx3hRCSIiIiLlyUpYPXv2xKZNm4rdlYGezrBAzbLQRSU4jYGIiIhIebKmMdjb2yM6OhodO3aEn58f7OzsjG7X6XSYM2eOIgVqkV7abuzR1mNcoEZERESkPFlh97vvvoOTkxP0en2xOzLoGNyeqPDWY5zGQERERFR+ZIXdffv2KV2Hpuj1AkfPJSLjrzjY37tW5Harm2loY5uO5+/8DZGXC4D/QSAiIiIqD7LCLj3ZqUsp+GzdEcxx+Rp2urwit9cEAEcAfwGGWc86K9tnWCERERFRxcCwWw5S07NhrcuXgu4Nu3oQ/xi5tbSwQG03J9jZWMKmpiesnKuZolQiIiIiTWPYLQd6vYAFHu1U0W7sJ9BZstVEREREzxpXRZUDIQR0hcIuF58RERERmQZTWDnI18NoZJd76BIRERGZBlNYOTAa2WXQJSIiIjIZJrFyoGfYJSIiIjILTGLlQOgFLHQPr5LG/XOJiIiITIZhtxzkFx7Z5eI0IiIiIpNhEisHQhRaoMaRXSIiIiKTYdgtB3q9gCHicicGIiIiItNhEisHBReV0Bd8wmkMRERERCbDJFYO9OLRAjXuxkBERERkOkxi5aBg67ECnMZAREREZDpMYuVACEBnmMbABWpEREREJsOwWw4KL1DjNAYiIiIi02ESKwd6IaStx3hRCSIiIiLTYdgtB/pCV1DjbgxEREREpsMkVg4K5uxyNwYiIiIiU2MSKwcF++wapjGwxURERESmwiRWDgq2HuM0BiIiIiJTYxIrB4UXqHHrMSIiIiLTUUXYTU1NxUcffYT27dujWbNmePPNN3HixAlTl/VYBVuPcRoDERERkampIomNHz8ef/75JyIiIrB161b4+vpi6NChuHLliqlLK5YQgI6XCyYiIiIyObNPYlevXsWhQ4cwc+ZMNG/eHHXr1sWHH36IGjVqYOfOnaYur1iFF6gx7BIRERGZjpWpC3gaFxcXrFy5En5+ftIxnU4HnU6He/fuyTqnEAIZGRlKlQgAyMzMBABcu3UX/ztyGaOdzhQ8F5R/LnNl6IHh74qIPWAPAPYAYA8A9gBQtgdCCF6oiWTRCSGEqYsorR9//BHvvfceVqxYgcDAwFI99syZM8jJySmfwgB8f/Qucq5dwHCn/QCA3Gp1kd7izXJ7PiIioorCxsbGaPCLqCTMfmT3n/744w+EhYWhU6dOpQ66BtbW1vDy8lK0rszMTCQkJMDKxh4WulzpuHu3EbCq+pyiz2WuDD3w8PCAvb29qcsxCfaAPQDYA4A9ANgDQNkexMXFKVQVVTSqCrs///wzJk6ciGbNmiE8PFz2eXQ6HRwcHBSsrNC5LSyknRjs/9UEzrWUDdVqYG9vX279VQv2gD0A2AOAPQDYA0CZHnAKA8mlmtVTGzduxJgxYxAUFITly5fD1tbW1CUVS68HLKAv+ISL04iIiIhMShVpbPPmzfj4448xcOBAREREwMbGxtQlPVbBBPqCj3W8ehoRERGRSZn9NIb4+HjMmTMHHTt2xDvvvIPbt29Lt9nZ2cHJycmE1RXFq6cRERERmQ+zD7s//vgjcnNz8dNPP+Gnn34yuq13796YN2+eiSornhCQ5uxyGgMRERGRaZl92B0xYgRGjBhh6jJKrPAFJXipYCIiIiLTYhpTmNE0Bs7ZJSIiIjIppjGFFZ7GwJFdIiIiItNiGlOYXi+g03GBGhEREZE5YNhVmF6IRwvUOI2BiIiIyKSYxhRmNGeX7SUiIiIyKaYxhen1hebscmSXiIiIyKSYxhQmjC4qwfYSERERmRLTmML0QsBCZ9iNgQvUiIiIiEyJYVdhotA0Bi5QIyIiIjItpjGFGS1Q48guERERkUkx7CpMrxe8qAQRERGRmWAaU5i+0BXUuECNiIiIyLSYxhRWsBvDQ5yzS0RERGRSTGMK04tHlwvmNAYiIiIi02IaU5heL2ABfcEnXKBGREREZFIMuwormLP7EEd2iYiIiEyKaUxhha+gxmkMRERERKZlZeoCtCI/Px/Jv+xEP/3fcLdJLTjIBWpEREREJsWwq5AbFy/CJ+sMYPPomGUlF9MVREREREQMu0rJy8mGLYD7ejs4tBuI555zhYNnU1OXRURERFShMewqRIiCebq5FjaoF9jVxNUQEREREcAFaooR+QXbjQm2lIiIiMhsMJkpRK/PBwAIcG9dIiIiInPBsKuUh9MYGHaJiIiIzAfDrkL0esM0BoZdIiIiInPBsKsQYQi7vEQwERERkdlg2FWKyH/4AVtKREREZC6YzBQi8h/O2eXILhEREZHZYNhViF5wzi4RERGRuWHYVYhhzi4YdomIiIjMBsOuUgQXqBERERGZG4ZdhUi7MbClRERERGaDyUwh0jQGjuwSERERmQ2GXaVIV1BjS4mIiIjMBZOZQoTgyC4RERGRuWHYVYjg1mNEREREZodhVyGcs0tERERkfhh2lWLYjUHHlhIRERGZCyYzhUhzdjmNgYiIiMhsqCLs6vV6LFmyBO3atUOTJk0wfPhwXL9+3dRlGZOmMaiipUREREQVgiqS2bJly7B582Z8/PHH+Oqrr6DX6zFs2DDk5OSYurRHDFuPcc4uERERkdkw+7Cbk5ODtWvX4r333kNgYCDq16+PhQsXIjExEf/73/9MXZ6E0xiIiIiIzI/Zh90LFy7gwYMHaN26tXTM2dkZDRo0wPHjx01YmTHxcGSX0xiIiIiIzIeVqQt4msTERACAu7u70fEaNWpIt5WWEAIZGRllrq0wfV5uwd+A4udWi8zMTKO/KyL2gD0A2AOAPQDYA0DZHgghoONUQZLB7MOu4R+IjY2N0XFbW1ukpaXJOmdubi5iYmLKXFthWVYOAIBMa2fFz602CQkJpi7B5NgD9gBgDwD2AGAPAOV68M8sQFQSZh927ezsABTM3TV8DADZ2dmwt7eXdU5ra2t4eXkpUp+Bh4cHzv5ZCy0bN4ajo6Oi51aLzMxMJCQkwMPDQ/bXRu3YA/YAYA8A9gBgDwBlexAXF6dQVVTRmH3YNUxfSE5ORp06daTjycnJ8PHxkXVOnU4HBwcHReorrJKLCxwdHcvl3Gpib2/PHrAH7AHYA4A9ANgDQJkecAoDyWX2q6nq16+PSpUq4ejRo9Kxe/fu4fz582jRooUJKyMiIiIic2f2I7s2NjYYNGgQwsPDUbVqVTz//POYP38+atasiU6dOpm6PCIiIiIyY2YfdgHgvffeQ15eHqZPn46srCy0aNECa9asgbW1talLIyIiIiIzpoqwa2lpiUmTJmHSpEmmLoWIiIiIVMTs5+wSEREREcnFsEtEREREmsWwS0RERESaxbBLRERERJrFsEtEREREmsWwS0RERESaxbBLRERERJrFsEtEREREmsWwS0RERESapRNCCFMX8Sz98ccfEELAxsZG0fMKIZCbmwtra2vodDpFz60W7AF7ALAHAHsAsAcAewAo24OcnBzodDo0a9ZMoeqoolDF5YKVVF7fcHQ6neIBWm3YA/YAYA8A9gBgDwD2AFC2BzqdrsL+p4HKpsKN7BIRERFRxcE5u0RERESkWQy7RERERKRZDLtEREREpFkMu0RERESkWQy7RERERKRZDLtEREREpFkMu0RERESkWQy7RERERKRZDLtEREREpFkMu0RERESkWQy7RERERKRZDLtEREREpFkMuwrQ6/VYsmQJ2rVrhyZNmmD48OG4fv26qctSTGpqKj766CO0b98ezZo1w5tvvokTJ05It4eGhsLHx8foT0hIiHR7dnY2Zs2ahdatW6Np06aYMGEC7ty5Y4qXIltSUlKR1+jj44Nt27YBAGJiYjBo0CA0adIEwcHBWL9+vdHj1f4eOXr0aLGv38fHB6+88goA4Isvvij29sI2bdqEV155Bf7+/hgwYADOnz9vipcjy4oVK4ze14AyX/enncOcFNeDffv2oW/fvmjatCmCg4Px2WefISsrS7o9Ojq62PfF0aNHpfscOXIEffr0QePGjdGlSxfs3r37mb2m0iquB9OnTy/y+oKDg6Xbtf4+CAkJeez3h+3btwMA8vPz4e/vX+T2yMhI6Tw3btzAO++8g2bNmqFt27ZYtGgR8vPzn/XLIy0SVGaRkZGiZcuWYv/+/SImJkYMGTJEdOrUSWRnZ5u6NEWEhoaKbt26iePHj4srV66IWbNmCX9/f3H58mUhhBCtW7cWmzdvFsnJydKfu3fvSo+fOnWq6NChgzh+/Lg4deqU6NWrlxg4cKCJXo08v/zyi/Dz8xNJSUlGrzMzM1PcuXNHtGzZUoSFhYm4uDjx7bffCj8/P/Htt99Kj1f7eyQ7O9vodScnJ4v//e9/wsfHR3qd77//vpg0aVKR+xls27ZN+Pv7ix07dohLly6JSZMmiYCAAPH333+b6mWV2MaNG0X9+vXFoEGDpGNKfN1Lcg5zUVwPjh8/Lnx9fcUXX3wh4uPjxS+//CLat28vpk6dKt1n06ZNokOHDkXeF4YexMXFCT8/PxERESHi4uLE6tWrRYMGDcThw4ef+Wt8muJ6IIQQr7/+uoiIiDB6fYXf11p/H9y9e9fotSclJYkBAwaI1157TaSnpwshCr7O3t7eIiYmxui+httzcnJEp06dxNtvvy0uXrwofvrpJxEQECAWL15sktdJ2sKwW0bZ2dmiadOmYtOmTdKxtLQ04e/vL3bu3GnCypSRkJAgvL29xYkTJ6Rjer1edOjQQSxatEjcvn1beHt7i3PnzhX7+MTERFG/fn3xyy+/SMeuXLkivL29xR9//FHu9Stl5cqVonv37sXetnz5ctG2bVuRm5srHVuwYIHo1KmTEEKb75EHDx6IoKAgo1Dz6quvii+//PKxj+nUqZP4/PPPpc9zc3PFyy+/LJYvX16epZZJYmKieOedd0STJk1Ely5djH7AK/F1f9o5zMGTejBhwgTx73//2+j+3333nWjYsKEU5GbMmCFGjBjx2PN/+OGH4vXXXzc6Nn78eDFkyBAFX0XZPKkHer1eNGnSRPzvf/8r9rEV4X3wTxs2bBCNGjWSBkSEEGL37t2iWbNmj33Mzp07RaNGjURqaqp07KuvvhLNmjVTzaAAmS9OYyijCxcu4MGDB2jdurV0zNnZGQ0aNMDx48dNWJkyXFxcsHLlSvj5+UnHdDoddDod7t27h4sXL0Kn06Fu3brFPj46OhoA0KpVK+lY3bp14ebmpqr+XLx4EZ6ensXeduLECQQEBMDKyko61qpVKyQkJOD27duafI8sX74cmZmZmDJlCgAgJycHCQkJ+Ne//lXs/f/++28kJCQY9cDKygrNmzc36x6cO3cO1tbW+P7779G4cWOj25T4uj/tHObgST0YMmSI9B4wsLCwQG5uLtLT0wE8+d8OUNCDwj0CCnoQHR0NIYRCr6JsntSDa9euISMj47Hv/YrwPijszp07WLRoEUaOHGnUk5K8Dxo2bIjKlStLx1q1aoX09HTExMQo8yKowrJ6+l3oSRITEwEA7u7uRsdr1Kgh3aZmzs7OePnll42O/fjjj7h69So++OADxMbGwsnJCbNnz8ahQ4fg4OCALl26YNSoUbCxsUFSUhJcXFxga2trdA619Sc2NhYuLi4YOHAg4uPj8cILL2DkyJFo3749EhMT4e3tbXT/GjVqAABu3bqluffInTt3sG7dOkyYMAFVqlQBAMTFxSE/Px8//vgjPv30U2RnZ6NFixaYNGmS0essrgcXLlx41i+hxIKDg43mXhamxNf9aeeoXr162V9EGT2pBw0aNDD6PDc3F+vWrUOjRo1QtWpVAMClS5fg4uKCPn36ICkpCd7e3hg3bhz8/f0BFPSgZs2aRuepUaMGMjMzcffuXek8pvSkHsTGxgIANmzYgF9//RUWFhZo3749xo0bBycnpwrxPihs1apVsLOzw9ChQ42Ox8bGIi8vD0OHDsWFCxfg5uaGwYMHo2fPngAe/z4ACnrwpIBN9DQc2S2jzMxMAICNjY3RcVtbW2RnZ5uipHL1xx9/ICwsDJ06dUJgYCBiY2ORnZ0Nf39/rF69GiNHjsSWLVswffp0AAX9+WdvAHX1Jy8vD1euXEFaWhrGjBmDlStXokmTJnj77bdx5MgRZGVlFfv1BwoW52ntPbJ582Y4OTmhf//+0jHDD3x7e3ssXrwYn376Ka5cuYK33noLWVlZmusBAEW+7k87h5rk5eVh8uTJuHTpEmbMmAGgIKTcv38fGRkZmD59OpYtW4bq1atj0KBBiIuLA1B8Dwyf5+TkPNsXIUNsbCwsLCxQo0YNLF++HFOnTsXBgwcxatQo6PX6CvU+SE9PxzfffIOhQ4cWGeC4dOkSUlNTERISgjVr1qBz584ICwvDt99+C0A7PSDzxJHdMrKzswNQ8E3Z8DFQ8I/T3t7eVGWVi59//hkTJ05Es2bNEB4eDgCYPXs2pkyZIv3qydvbG9bW1hg3bhwmT54MOzu7Yn9gqak/VlZWOHr0KCwtLaWvcaNGjXDp0iWsWbOm2Ndo+Obs4OCguffI9u3b0atXL6PX0qtXL7Rv395oFK5evXpo37499u3bhzp16gAoGl7U2gMAinzdn3YOtUhPT8fYsWNx7NgxREVFSaO27u7uOH78OOzt7WFtbQ0A8PPzw/nz57FhwwbMmjULtra2RXpg+FwN742RI0diwIABcHFxAVDwPdDV1RX9+vXDmTNnKtT74Oeff0ZOTg769u1b5LZdu3YhPz8fjo6OAID69evjr7/+wpo1a/D6669rpgdknjiyW0aGX00lJycbHU9OToabm5spSioXGzduxJgxYxAUFITly5dL/+O2srIymmMFFIQc4NGvpVJTU4t8E1NbfxwdHY1+UAEFrzMpKQk1a9Ys9usPAG5ubpp6j1y4cAHXr19H9+7di9z2z18316hRA1WqVEFiYqKmemCgxNf9aedQg+TkZAwcOBAnT57EmjVrikx7cnZ2loIuUDCn19PTE0lJSQAKvocW1wMHBwc4OTmV/wsoIwsLCynoGhT+HlhR3gdAQdh9+eWX4ezsXOQ2Ozs7KegaeHt7S1M5tNIDMk8Mu2VUv359VKpUyWjPyHv37uH8+fNo0aKFCStTzubNm/Hxxx9j4MCBiIiIMPpVU0hICMLCwozuf+bMGVhbW8PDwwMvvvgi9Hq9tFANAOLj45GUlKSa/ly6dAnNmjUz+hoDwNmzZ+Hl5YUWLVogOjraaD/I33//HXXr1kW1atU09R45ceKE9JoKW7hwITp37my0oOjGjRu4e/cuvLy8UK1aNdStW9eoB3l5eThx4oTqemCgxNf9aecwd2lpaRg8eDDu3LmDTZs2Ffla/vrrr2jatKnRnrJ5eXm4cOECvLy8AADNmzfHsWPHjB73+++/o1mzZrCwMP8fUZMnT8a///1vo2NnzpwBAHh5eVWI94FBcYsNgYLXGxAQIO1LbnDmzBnpPwYtWrTA+fPnpYWNQEEPHB0di3y/ISot8/9OYuZsbGwwaNAghIeHY+/evbhw4QLGjRuHmjVrolOnTqYur8zi4+MxZ84cdOzYEe+88w5u376NlJQUpKSk4P79++jcuTN27NiB//73v7h+/Tr27NmDzz//HEOHDkWlSpXg5uaG1157DdOnT8fRo0dx+vRpjB8/HgEBAWjSpImpX16JeHp64l//+hdmz56NEydO4PLly5g7dy5OnjyJkSNHom/fvkhPT8e0adMQFxeHbdu2Yd26dXjnnXcAaOs9cv78+SIXigCAjh074ubNm5g5cybi4+Nx/PhxjBkzBs2aNUO7du0AFKzc//LLL/Hdd98hLi4OH3zwAbKysvD6668/65ehCCW+7k87h7mbO3curl+/jvnz56Nq1arS94aUlBTk5+ejWbNmcHFxwZQpU3D27FlcvHgRU6ZMQWpqqhQQQ0JCcPr0aYSHh+Py5ctYu3YtfvjhBwwbNsy0L66EOnfujCNHjiAqKgrXrl3DgQMH8MEHH6Bbt27w9PSsEO8DoGB+9t27d4sNps7OzmjVqhUWLlyIAwcOICEhAStXrsT333+PMWPGAAA6dOgAV1dXjB07FhcuXMDPP/+MiIgIDBkypNh1H0SlYuq9z7QgLy9PfP7556JVq1aiSZMmYvjw4eL69eumLksRX3zxhfD29i72z5QpU4QQBZuMv/rqq6JRo0YiKChIfPHFFyI/P186x4MHD8S0adNE8+bNRfPmzcX48ePFnTt3TPWSZElJSRFTp04Vbdq0EX5+fqJ///7i+PHj0u2nTp0S/fr1k3qwYcMGo8dr5T0ybNgwMXbs2GJvO3z4sOjfv79o0qSJCAgIEGFhYUZ7ZgohxOrVq0X79u2Fv7+/GDBggDh//vyzKFsRU6ZMKbK3qBJf96edw5wU7kFeXp7w8/N77PcHw+u8evWqGDNmjAgICBCNGzcWQ4YMERcvXjQ674EDB0S3bt1Eo0aNRJcuXcTu3buf+WsrqeLeB3v27BG9evUS/v7+ok2bNmLevHkiKytLul3L7wODU6dOCW9vbxEXF1fsY+7fvy/mzJkjXn75ZdGoUSPRs2dP8dNPPxndJyEhQYSGhgo/Pz/Rtm1bsWjRIqOfJURy6YQwk40MiYiIiIgUxmkMRERERKRZDLtEREREpFkMu0RERESkWQy7RERERKRZDLtEREREpFkMu0RERESkWQy7RERERKRZDLtEpFncRpyIiBh2iUiToqOj8fbbb5u6DCIiMjGGXSLSpC1btuDy5cumLoOIiEyMYZeIiIiINIthl4gUtWXLFrz22mto1KgRAgMDERkZifz8fOzcuRM+Pj6IjY01uv/PP/8MHx8fnD9/HgCQmpqKjz76CC+99BL8/PzQr18/HDlyxOgxPj4+2LRpE6ZNm4aAgAA0bdoU77//Pm7fvg0AmDp1Kr777jvcvHkTPj4+2LZtW4nrDw4OxpIlS/DZZ5/hpZdegr+/P4YOHYqEhASj+x06dAgDBgzAiy++iJYtW2LChAm4deuWjI4REVF5YtglIsWsWLECH374IVq3bo3ly5dj4MCBWLVqFT788EN06NABDg4O2L17t9Fjdu3ahXr16qFBgwbIzs7G4MGDsXfvXowbNw5RUVGoWbMmhg0bViTwLly4EHq9HhEREZg8eTL279+POXPmAABGjRqFl19+Ga6urvj6668RGBhYqtexfv16XLlyBXPnzsUnn3yCs2fPYsqUKdLt27dvx5AhQ+Du7o6IiAiEhYXhzz//RP/+/fH333/Lax4REZULK1MXQETacP/+fSxbtgz9+/fH9OnTAQBt27ZFlSpVMH36dISGhqJz587Ys2cPxo0bBwB48OAB9u/fj3fffRcAsGPHDly4cAHffPMNGjduDABo3749QkJCEB4ejq1bt0rP5+3tjblz50qfnz59Gj/88AMAoE6dOqhatSpsbGzQpEmTUr8WZ2dnLFu2DJaWlgCAa9euITIyEnfv3kXlypURHh6Otm3bYsGCBdJjmjVrhq5du2LNmjWYPHlyqZ+TiIjKB0d2iUgRf/75J7KyshAcHIy8vDzpT3BwMICCX/v37NkT165dw+nTpwEAe/fuRU5ODnr06AEAOHLkCFxdXdGwYUPp8fn5+QgKCsLZs2eRlpYmPd8/Q2zNmjWRmZmpyGvx8/OTgq7h3ACQmZmJ+Ph4pKSkoFu3bkaPqVOnDpo2bYpjx44pUgMRESmDI7tEpIjU1FQAeOx2X8nJyXjrrbfg5uaG3bt3w9/fH7t370ZAQIAUJlNTU5GSkoKGDRsWe46UlBRUrlwZAGBvb290m4WFhWL76hZ3bgDQ6/XS66xevXqRx1WvXl2ae0xEROaBYZeIFOHs7AwACA8Ph4eHR5Hbq1evDgsLC3Tv3h27du3CiBEjcOjQIcyePVu6j5OTEzw8PBAeHl7sc9SqVatcai+NKlWqAIC0GK6wlJQUuLi4POOKiIjoSTiNgYgU0bhxY1hbWyMpKQl+fn7SHysrK0RERODGjRsAgJ49eyIxMRFLly6FpaUlOnXqJJ0jICAAt27dQrVq1YzOcejQIaxevdpoasHTGEZjlVa3bl24urpi165dRsevX7+OkydPolmzZuXyvEREJA9HdolIES4uLhg2bBgWL16M9PR0tGzZEklJSVi8eDF0Oh3q168PoGBhma+vLzZv3oxXX30VlSpVks7Rp08fbNy4EaGhoRgxYgTc3d1x+PBhrFq1CoMGDYK1tXWJ63F2dsbt27dx4MAB+Pr6okaNGoq8TgsLC4wfPx5hYWGYMGECevTogbt37yIqKgqVK1dGaGioIs9DRETKYNglIsWMHTsWrq6u2Lx5M1avXo3KlSujdevWGD9+PJycnKT79ezZE/PmzZMWphk4ODhg06ZNWLBgAebPn4/79+/j+eefx4QJEzBkyJBS1dKnTx8cOHAA7777Lt577z1FLx3cp08fODo6YsWKFXj33XdRqVIltGvXDuPHj4erq6tiz0NERGWnE0qt6CAiIiIiMjMc2SUizdPr9dDr9U+9n5UVvyUSEWkNv7MTkeYtXboUUVFRT73f3r17zWLHByIiUg6nMRCR5iUlJSE5Ofmp9/Px8YGNjc0zqIiIiJ4Vhl0iIiIi0izus0tEREREmsWwS0RERESaxbBLRERERJrFsEtEREREmsWwS0RERESaxbBLRERERJrFsEtEREREmvX/Ae26yiI6xfcsAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "df_time = pd.DataFrame(time_results)\n",
    "\n",
    "# com.money.manager.ex_1032\t\n",
    "# familyfinance\n",
    "# com.ichi2.anki_21803300\n",
    "ax = sns.lineplot(data=df_time[df_time.app_id == 'com.money.manager.ex_1032'], x='event_no', y='num_covered_activities', hue='technique')\n",
    "sns.move_legend(ax, \"upper left\", bbox_to_anchor=(1, 1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_time = pd.DataFrame(time_results)\n",
    "\n",
    "\n",
    "# org.tasks_130909\n",
    "ax = sns.lineplot(data=df_time[df_time.app_id == 'org.tasks_130909'], x='event_no', y='num_covered_activities', hue='technique')\n",
    "sns.move_legend(ax, \"upper left\", bbox_to_anchor=(1, 1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_time = pd.DataFrame(time_results)\n",
    "\n",
    "ax = sns.lineplot(data=df_time[df_time.app_id == 'com.nextcloud.talk2_190000190'], x='event_no', y='num_covered_activities', hue='technique')\n",
    "sns.move_legend(ax, \"upper left\", bbox_to_anchor=(1, 1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [],
   "source": [
    "abbr_map = {\n",
    "    'oss.krtirtho.spotube_31': 'Spotube',\n",
    "    'luci.sixsixsix.powerampache2.fdroid_59': 'AmpachePlayer',\n",
    "    'com.money.manager.ex_1032': 'MoneyManager',\n",
    "    'com.nextcloud.talk2_190000190': 'NextCloudTalk',\n",
    "    'lying.fengfeng.foodrecords_1': 'FoodRecords',\n",
    "    'org.asafonov.monly_47': 'Monly',\n",
    "    'org.tasks_130909': 'Tasks',\n",
    "    'com.ichi2.anki_21803300': 'AnkiDroid',\n",
    "    'com.moimob.drinkable_15000': 'Drinkable',\n",
    "    'moe.dic1911.urlsanitizer_30': 'URLSanitizer',\n",
    "    'aeroflot': 'Aeroflot',\n",
    "    'familyfinance': 'FamilyFinance'\n",
    "}\n",
    "\n",
    "result_df['activity_coverage'] = result_df.apply(lambda x: x['num_internal_activities'] / x['num_all_activities'], axis=1)\n",
    "result_df['name'] = result_df.apply(lambda x: abbr_map[x['app']], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1000x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns \n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.figure(figsize=(10, 3))\n",
    "\n",
    "sns.set(style=\"whitegrid\")\n",
    "\n",
    "ax = sns.barplot(x=\"name\", y=\"num_internal_activities\", hue=\"technique\", data=result_df, palette=\"Set2\")\n",
    "ax.set_xlabel('')\n",
    "ax.set_ylabel('# of reached activities')\n",
    "# x label rotation \n",
    "plt.xticks(rotation=80)\n",
    "\n",
    "# hide legend title \n",
    "plt.legend(title='', loc='upper left')\n",
    "# plt.savefig('/Users/greenmon/Dropbox/COINSE/DroidFiller/figures/RQ4_activity_coverage.pdf', bbox_inches='tight')\n",
    "plt.savefig('/Users/greenmon/Dropbox/COINSE/DroidFiller/figures/RQ4_activity_coverage.pdf', bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x10a403100>"
      ]
     },
     "execution_count": 122,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1000x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns \n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.figure(figsize=(10, 3))\n",
    "\n",
    "sns.set(style=\"whitegrid\")\n",
    "\n",
    "ax = sns.barplot(x=\"name\", y=\"activity_coverage\", hue=\"technique\", data=result_df, palette=\"Set2\")\n",
    "ax.set_xlabel('')\n",
    "ax.set_ylabel('Number of reached activities')\n",
    "# x label rotation \n",
    "plt.xticks(rotation=80)\n",
    "\n",
    "# hide legend title \n",
    "plt.legend(title='', loc='upper left')\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1000x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns \n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.figure(figsize=(10, 3))\n",
    "\n",
    "sns.set(style=\"whitegrid\")\n",
    "\n",
    "ax = sns.barplot(x=\"name\", y=\"num_covered_states\", hue=\"technique\", data=result_df, palette=\"Set2\")\n",
    "# ax.set_title('State Coverage Comparison')\n",
    "ax.set_xlabel('')\n",
    "ax.set_ylabel('# of covered states')\n",
    "# x label rotation \n",
    "plt.xticks(rotation=80)\n",
    "\n",
    "# hide legend title \n",
    "plt.legend(title='', loc='upper left')\n",
    "plt.savefig('/Users/greenmon/Dropbox/COINSE/DroidFiller/figures/RQ4_state_coverage.pdf', bbox_inches='tight')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>app</th>\n",
       "      <th>AC_delta_absolute</th>\n",
       "      <th>CC_delta_absolute</th>\n",
       "      <th>AC_delta</th>\n",
       "      <th>CC_delta</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>aeroflot</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>25.00</td>\n",
       "      <td>0.72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>com.ichi2.anki_21803300</td>\n",
       "      <td>4</td>\n",
       "      <td>73</td>\n",
       "      <td>36.36</td>\n",
       "      <td>29.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>com.moimob.drinkable_15000</td>\n",
       "      <td>0</td>\n",
       "      <td>26</td>\n",
       "      <td>0.00</td>\n",
       "      <td>144.44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>com.money.manager.ex_1032</td>\n",
       "      <td>-2</td>\n",
       "      <td>37</td>\n",
       "      <td>-13.33</td>\n",
       "      <td>3.51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>com.nextcloud.talk2_190000190</td>\n",
       "      <td>1</td>\n",
       "      <td>78</td>\n",
       "      <td>100.00</td>\n",
       "      <td>1114.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>familyfinance</td>\n",
       "      <td>7</td>\n",
       "      <td>-6</td>\n",
       "      <td>35.00</td>\n",
       "      <td>-3.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>luci.sixsixsix.powerampache2.fdroid_59</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>lying.fengfeng.foodrecords_1</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>0.00</td>\n",
       "      <td>19.23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>moe.dic1911.urlsanitizer_30</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.00</td>\n",
       "      <td>6.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>org.asafonov.monly_47</td>\n",
       "      <td>0</td>\n",
       "      <td>-19</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-8.41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>org.tasks_130909</td>\n",
       "      <td>0</td>\n",
       "      <td>412</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1872.73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>oss.krtirtho.spotube_31</td>\n",
       "      <td>0</td>\n",
       "      <td>20</td>\n",
       "      <td>0.00</td>\n",
       "      <td>9.66</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                       app  AC_delta_absolute  \\\n",
       "0                                 aeroflot                  2   \n",
       "1                  com.ichi2.anki_21803300                  4   \n",
       "2               com.moimob.drinkable_15000                  0   \n",
       "3                com.money.manager.ex_1032                 -2   \n",
       "4            com.nextcloud.talk2_190000190                  1   \n",
       "5                            familyfinance                  7   \n",
       "6   luci.sixsixsix.powerampache2.fdroid_59                  0   \n",
       "7             lying.fengfeng.foodrecords_1                  0   \n",
       "8              moe.dic1911.urlsanitizer_30                  0   \n",
       "9                    org.asafonov.monly_47                  0   \n",
       "10                        org.tasks_130909                  0   \n",
       "11                 oss.krtirtho.spotube_31                  0   \n",
       "\n",
       "    CC_delta_absolute  AC_delta  CC_delta  \n",
       "0                   4     25.00      0.72  \n",
       "1                  73     36.36     29.67  \n",
       "2                  26      0.00    144.44  \n",
       "3                  37    -13.33      3.51  \n",
       "4                  78    100.00   1114.29  \n",
       "5                  -6     35.00     -3.05  \n",
       "6                   3      0.00      2.56  \n",
       "7                  15      0.00     19.23  \n",
       "8                   2      0.00      6.45  \n",
       "9                 -19      0.00     -8.41  \n",
       "10                412      0.00   1872.73  \n",
       "11                 20      0.00      9.66  "
      ]
     },
     "execution_count": 124,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "delta_results = []\n",
    "\n",
    "for app, group_df in result_df.groupby('app'):\n",
    "    droidfiller_AC = group_df[group_df.technique == 'STEM+DroidFiller'].num_internal_activities.tolist()[0]\n",
    "    droidfiller_CC = group_df[group_df.technique == 'STEM+DroidFiller'].num_covered_states.tolist()[0]\n",
    "\n",
    "    context_AC = group_df[group_df.technique == 'STEM+Context'].num_internal_activities.tolist()[0]\n",
    "    context_CC = group_df[group_df.technique == 'STEM+Context'].num_covered_states.tolist()[0]\n",
    "\n",
    "    delta_results.append({\n",
    "        'app': app,\n",
    "        'AC_delta_absolute': (droidfiller_AC - context_AC),\n",
    "        'CC_delta_absolute': (droidfiller_CC - context_CC),\n",
    "        'AC_delta': round((droidfiller_AC - context_AC) / context_AC * 100, 2),\n",
    "        'CC_delta': round((droidfiller_CC - context_CC) / context_CC * 100, 2),\n",
    "    })\n",
    "\n",
    "pd.DataFrame(delta_results)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "sr-stem",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}