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<!--
Copyright © 2019, empirical software engineering team from Peking Uninversity and ISCAS, All rights reserved.
Written by:
Jiaxin Zhu
-->
<script src='js/header.js'></script>
<main role="main">
<section class="jumbotron">
<div class="container">
<div class="row">
<div class="col-md-3">
<div class="card my-4">
<div class="card-header">
数据类型
</div>
<ul class="list-group list-group-flush">
<li class="list-group-item"><input type="checkbox"> VCS(0) </li>
<li class="list-group-item"><input type="checkbox"> ITS(0) </li>
<li class="list-group-item"><input type="checkbox"> Mails(0) </li>
</ul>
</div>
<div class="card my-4">
<div class="card-header">
数据规模
</div>
<ul class="list-group list-group-flush">
<li class="list-group-item"><input type="checkbox"> <=500M(8) </li>
<li class="list-group-item"><input type="checkbox"> >500M <=1G(2) </li>
<li class="list-group-item"><input type="checkbox"> >1G(30) </li>
</ul>
</div>
<div class="card my-4">
<div class="card-header">
流行度
</div>
<ul class="list-group list-group-flush">
<li class="list-group-item"><input type="checkbox"> <=100(40) </li>
<li class="list-group-item"><input type="checkbox"> >100 <=500(0) </li>
<li class="list-group-item"><input type="checkbox"> >500(0) </li>
</ul>
</div>
</div>
<div class="col-md-9">
<hr class="no-margin-top">
<div class="row">
<div class="col-md-12">
<div class="float-right">
<a class="btn btn-outline-secondary btn-sm" href="https://zenodo.org/record/1154905">View</a>
</div>
</div>
<div class="w"></div>
<div class="col-md-12">
<h4>
<a>igorsteinmacher/ICSE_QuasiContributors</a>
</h4>
<p>
<span class="dataset-author">
<a>Igor Steinmacher</a>;
</span>
<span class="dataset-author">
<a>Gustavo Pinto</a>;
</span>
<span class="dataset-author">
<a>Igor Wiese</a>;
</span>
<span class="dataset-author">
<a>Marco Gerosa</a>;
</span>
</p>
<p>
No description provided.
</p>
</div>
</div>
<hr class="no-margin-top">
<div class="row">
<div class="col-md-12">
<div class="float-right">
<a class="btn btn-outline-secondary btn-sm" href="https://zenodo.org/record/1166022">View</a>
</div>
</div>
<div class="w"></div>
<div class="col-md-12">
<h4>
<a>Search-Based Test Data Generation for SQL Queries: Appendix</a>
</h4>
<p>
<span class="dataset-author">
<a>Jeroen Castelein</a>;
</span>
<span class="dataset-author">
<a>Maurício Aniche</a>;
</span>
<span class="dataset-author">
<a>Mozhan Soltani</a>;
</span>
<span class="dataset-author">
<a>Annibale Panichella</a>;
</span>
<span class="dataset-author">
<a>Arie van Deursen</a>;
</span>
</p>
<p>
The appendix of our ICSE 2018 paper /"Search-Based Test
Data Generation for SQL Queries: Appendix/".The appendix contains: The
queries from the three open source systems we used in the evaluation of
our tool /(the industry software system is not part of this appendix,
due to privacy reasons/) The results of our evaluation. The source code
of the tool. Most recent version can be found
at/ https:////github.com//SERG-Delft//evosql. The results of the
tuning procedure we conducted before running the final evaluation.
</p>
</div>
</div>
<hr class="no-margin-top">
<div class="row">
<div class="col-md-12">
<div class="float-right">
<a class="btn btn-outline-secondary btn-sm" href="https://zenodo.org/record/1156931">View</a>
</div>
</div>
<div class="w"></div>
<div class="col-md-12">
<h4>
<a>ICSE 2018 and ICPC 2019 Research Dataset on Live Programming</a>
</h4>
<p>
<span class="dataset-author">
<a>Juraj Kubelka</a>;
</span>
<span class="dataset-author">
<a>Romain Robbes</a>;
</span>
<span class="dataset-author">
<a>Alexandre Bergel</a>;
</span>
</p>
<p>
The release includes a dataset analyzed in the two
following research works:/ /"The Road to Live Programming: Insights
From the Practice./" /(ICSE 2018/)Abstract: Live Programming
environments allow programmers to get feedback instantly while changing
software. Liveness is gaining attention among industrial and open-source
communities; several IDEs offer high degrees of liveness. While several
studies looked at how programmers work during software evolution tasks,
none of them consider live environments. We conduct such a study based
on an analysis of 17 programming sessions of practitioners using Pharo, a
mature Live Programming environment. The study is complemented by a
survey and subsequent analysis of 16 programming sessions in additional
languages, e.g., JavaScript. We document the approaches taken by
developers during their work. We find that some liveness features are
extensively used, and have an impact on the way developers navigate
source code and objects in their work./"Live Programming and Software
Evolution: Questions during a Programming Change Task/" /(ICPC
2019/)Abstract:/ Several studies provide the questions developers
ask during software evolution tasks, providing foundations for
subsequent work. Nevertheless, none of them focus on Live Programming
environments that gain in popularity as they are perceived to have a
positive effect on programming tasks. Studying the impact of a Live
Programming environment on software development activities is thus the
goal of this study.In a partial replication of the study by
Sillito/ et al., we conducted 17 software evolution sessions in a
Live Programming environment and report 1,161 developer questions asked
during these sessions. We contrast our results with the results by
Sillito et al., focusing on the question occurrences, question
complexity and what information participants used to gain a required
knowledge. We report eight new questions and observe that the Live
Programming facilities do have an impact on the way developers ask
questions about source code and use tools to gain corresponding
knowledge.
</p>
</div>
</div>
<hr class="no-margin-top">
<div class="row">
<div class="col-md-12">
<div class="float-right">
<a class="btn btn-outline-secondary btn-sm" href="https://zenodo.org/record/776237">View</a>
</div>
</div>
<div class="w"></div>
<div class="col-md-12">
<h4>
<a>User-Profiling Dataset</a>
</h4>
<p>
<span class="dataset-author">
<a>Curro, Domenic</a>;
</span>
<span class="dataset-author">
<a>Derpanis, Konstantinos G.</a>;
</span>
<span class="dataset-author">
<a>Miranskyy, Andriy V.</a>;
</span>
</p>
<p>
The User-Profiling Dataset provides hand labeled user
action videos and frames. The dataset includes over 40k images from 236
video clips containing five different user actions, and five different
sequences of actions.
</p>
</div>
</div>
<hr class="no-margin-top">
<div class="row">
<div class="col-md-12">
<div class="float-right">
<a class="btn btn-outline-secondary btn-sm" href="https://zenodo.org/record/629853">View</a>
</div>
</div>
<div class="w"></div>
<div class="col-md-12">
<h4>
<a>Assessing Iterative Practical Software Engineering Courses with Play Money (Raw data of survey)</a>
</h4>
<p>
<span class="dataset-author">
<a>Ostberg, Jan-Peter </a>;
</span>
<span class="dataset-author">
<a>Minderman, Kai</a>;
</span>
<span class="dataset-author">
<a>Wagner, Stefan</a>;
</span>
</p>
<p>
This is the raw data of the surveys conducted for a
paper // poster /"/ Assessing Iterative Practical Software
Engineering Courses with Play Money/" at the ICSE 2016.
</p>
</div>
</div>
<hr class="no-margin-top">
<div class="row">
<div class="col-md-12">
<div class="float-right">
<a class="btn btn-outline-secondary btn-sm" href="https://zenodo.org/record/1167837">View</a>
</div>
</div>
<div class="w"></div>
<div class="col-md-12">
<h4>
<a>How Modern News Aggregators Help Development Communities Shape and Share Knowledge: Appendix</a>
</h4>
<p>
<span class="dataset-author">
<a>Maurício Aniche</a>;
</span>
<span class="dataset-author">
<a>Christoph Treude</a>;
</span>
<span class="dataset-author">
<a>Igor Steinmacher</a>;
</span>
<span class="dataset-author">
<a>Igor Wiese</a>;
</span>
<span class="dataset-author">
<a>Gustavo Henrique Lima Pinto</a>;
</span>
<span class="dataset-author">
<a>Margaret-Anne Storey</a>;
</span>
<span class="dataset-author">
<a>Marco Aurélio Gerosa</a>;
</span>
</p>
<p>
This package contains the appendix of our ICSE 2018
paper /"How Modern News Aggregators Help Development Communities Shape
and Share Knowledge/".Content: The qualitative analysis of the
interviews as well as the interview guide Data from HackerNews and
Reddit used in our quantitative analysis Results from our survey The
qualitative analysis on HN and Reddit posts
</p>
</div>
</div>
<hr class="no-margin-top">
<div class="row">
<div class="col-md-12">
<div class="float-right">
<a class="btn btn-outline-secondary btn-sm" href="https://zenodo.org/record/971161">View</a>
</div>
</div>
<div class="w"></div>
<div class="col-md-12">
<h4>
<a>what make long term contributors -- mozilla and gnome</a>
</h4>
<p>
<span class="dataset-author">
<a>zhou,minghui</a>;
</span>
</p>
<p>
Data and scripts for: Minghui Zhou, Audris Mockus: Who
Will Stay in the FLOSS Community? Modeling Participant's Initial
Behavior. Software Engineering, IEEE Transactions on , vol.41, no.1,
pp.82-99, Jan. 1 2015.Minghui Zhou and Audris Mockus. What Make Long
Term Contributors: Willingness and Opportunity in OSS Community. ICSE
'12 Proceedings of the 34rd International Conference on Software
Engineering, Zurich, Switzerland, 2-9 June 2012, pp.518-528.
</p>
</div>
</div>
<hr class="no-margin-top">
<div class="row">
<div class="col-md-12">
<div class="float-right">
<a class="btn btn-outline-secondary btn-sm" href="https://zenodo.org/record/786645">View</a>
</div>
</div>
<div class="w"></div>
<div class="col-md-12">
<h4>
<a>Opinions on Internal and External Validity</a>
</h4>
<p>
<span class="dataset-author">
<a>Janet Siegmund</a>;
</span>
<span class="dataset-author">
<a>Norbert Siegmund</a>;
</span>
<span class="dataset-author">
<a>Sven Apel</a>;
</span>
</p>
<p>
Overview of Data1/) studies.csv : Literature survey of
papers from ESEC//FSE, ICSE, and EMSE. Contains data on how they were
validated./<br ///>2/) resultsComplete.csv : Contains the
responses of the program-committee members and our categorization of the
responses.Attribute Information1/) studies.csv:/<br ///>Contains
name of the paper, conference and response for the following 5
questions/<br ///>- Was an empirical method applied?/<br
///>- Were the experimental subjects human or non-human?/<br
///>- Were the human experimental subjects professionals or
students?/<br ///>- Was an internal or external replication
reported?/<br ///>- How are threats to validity described?/<br
///>/<br ///>2/) resultsComplete.csv/<br ///>Contains the
responses of the program-committee members and our categorization of
the responses/<br ///>
</p>
</div>
</div>
<hr class="no-margin-top">
<div class="row">
<div class="col-md-12">
<div class="float-right">
<a class="btn btn-outline-secondary btn-sm" href="https://zenodo.org/record/758125">View</a>
</div>
</div>
<div class="w"></div>
<div class="col-md-12">
<h4>
<a>nasa93</a>
</h4>
<p>
<span class="dataset-author">
<a>Tim Menzies</a>;
</span>
</p>
<p>
None with this specific data set. But for older work on
similar data, see: “Validation Methods for Calibrating Software Effort
Models”, T. Menzies and D. Port and Z. Chen and J. Hihn and S. Stukes,
Proceedings ICSE 2005,http:////menzies.us//pdf//04coconut.pdf Results:
Given background knowledge on 60 prior projects, a new cost model can be
tuned to local data using as little as 20 new projects. A very simple
calibration method /(COCONUT/) can achieve PRED/(30/)=7/% or
PRED/(20/)=50/% /(after 20 projects/). These are results seen in 30
repeats of an incremental cross-validation study. Two cost models are
compared; one based on just lines of code and one using over a dozen
“effort multipliers”. Just using lines of code loses 10 to 20 PRED/(N/)
points. Additional Usage: “Feature Subset Selection Can Improve Software
Cost Estimation Accuracy” Zhihao Chen, Tim Menzies, Dan Port and Barry
Boehm Proceedings PROMISE Workshop
2005,http:////promise.site.uottawa.ca//proceedings//pdf//1.pdf P02, P03,
P04 are used in this paper. Results To the best of our knowledge, this
is the first report of applying feature subset selection /(FSS/) to
software effort data. FSS can dramatically improve cost estimation.
T-tests are applied to the results to demonstrate that always in our
data sets, removing attributes improves performance without increasing
the variance in model behavior.
</p>
</div>
</div>
<hr class="no-margin-top">
<div class="row">
<div class="col-md-12">
<div class="float-right">
<a class="btn btn-outline-secondary btn-sm" href="https://zenodo.org/record/639050">View</a>
</div>
</div>
<div class="w"></div>
<div class="col-md-12">
<h4>
<a>Efficient Large-Scale Trace Checking Using MapReduce</a>
</h4>
<p>
<span class="dataset-author">
<a>Marcello M. Bersani</a>;
</span>
<span class="dataset-author">
<a>Domenico Bianculli</a>;
</span>
<span class="dataset-author">
<a>Carlo Ghezzi</a>;
</span>
<span class="dataset-author">
<a>Srdan Krstic</a>;
</span>
<span class="dataset-author">
<a>Pierluigi San Pietro</a>;
</span>
</p>
<p>
The problem of checking a logged event trace against a
temporal logic specification arises in many practical cases.
Unfortunately, known algorithms for an expressive logic like MTL
/(Metric Temporal Logic/) do not scale with respect to two crucial
dimensions: the length of the trace and the size of the time interval
for which logged events must be buffered to check satisfaction of the
specification. The former issue can be addressed by distributed and
parallel trace checking algorithms that can take advantage of modern
cloud computing and programming frameworks like MapReduce. Still, the
latter issue remains open with current state-of-the-art
approaches./ In this paper we address this memory scalability issue
by proposing a new semantics for MTL, called lazy semantics. This
semantics can evaluate temporal formulae and boolean combinations of
temporal-only formulae at any arbitrary time instant. We prove that lazy
semantics is more expressive than standard point-based semantics and
that it can be used as a basis for a correct parametric decomposition of
any MTL formula into an equivalent one with smaller, bounded time
intervals. We use lazy semantics to extend our previous distributed
trace checking algorithm for MTL. We evaluate the proposed algorithm in
terms of memory scalability and time//memory tradeoffs.
</p>
</div>
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