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Expand Up @@ -74,19 +74,22 @@ The official book of the course, <cite><a href="https://comp-think.github.io/">C
- Chapter "How To Use List Methods": introductory paragraphs and sections "list.append()", "list.extend()", "list.remove()"
- Python: [define_functions.py](https://comp-think.github.io/python/define_functions.py), [list_instructions.py](https://comp-think.github.io/python/list_instructions.py), [stack_instructions.py](https://comp-think.github.io/python/stack_instructions.py), [queue_instructions.py](https://comp-think.github.io/python/queue_instructions.py)
- exercises: [1](https://github.com/comp-think/2024-2025/issues/15), [2](https://github.com/comp-think/2024-2025/issues/16), [3](https://github.com/comp-think/2024-2025/issues/17)
- solutions: [1](https://comp-think.github.io/keys/05/exercise-1), [2](https://comp-think.github.io/keys/05/exercise-2), [3](https://comp-think.github.io/keys/05/exercise-3)
<hr />
8. [15/11/24, *lab*] Laboratory: 2nd Lesson
- book chapter: [HTML](https://comp-think.github.io/laboratory/chapter/02)
<hr />
9. [18/11/24, *the*] Brute-force algorithms
- book chapter: [PDF](https://comp-think.github.io/book/06.pdf), [Google Docs](https://comp-think.github.io/book/06)
- slides: [HTML](https://comp-think.github.io/2024-2025/slides/06%20-%20Brute-force%20algorithms.html)
- from [How To Code in Python](https://www.digitalocean.com/community/books/digitalocean-ebook-how-to-code-in-python):
- Chapter "How To Construct While Loops": all content
- Chapter "How To Construct For Loops": all content
- Chapter "Understanding Tuples": all content
- Chapter "Understanding Lists": section "Constructing a List with List Items"
- Chapter "How To Use List Methods": section "list.insert()"
- Python: [stack_from_list.py](https://comp-think.github.io/python/stack_from_list.py), [run_forever.py](https://comp-think.github.io/python/run_forever.py), [linear_search.py](https://comp-think.github.io/python/linear_search.py), [insertion_sort.py](https://comp-think.github.io/python/insertion_sort.py)
- exercises: [1](https://github.com/comp-think/2024-2025/issues/18), [2](https://github.com/comp-think/2024-2025/issues/19), [3](https://github.com/comp-think/2024-2025/issues/20), [4](https://github.com/comp-think/2024-2025/issues/21), [5](https://github.com/comp-think/2024-2025/issues/22)
<hr />
10. [20/11/24, *the*] Organising information: unordered structures
- book chapter: [PDF](https://comp-think.github.io/book/07.pdf), [Google Docs](https://comp-think.github.io/book/07)
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<title>Brute-force algorithms</title>

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<section id="title" class="title_slide" role="doc-cover">
<h1>Brute-force algorithms</h1>
<div class="author">
<p><a href="https://www.unibo.it/sitoweb/silvio.peroni/en">Silvio Peroni</a></p>
<p class="contact">
<i class="fa fa-envelope" aria-hidden="true"></i> <a href="mailto:[email protected]">[email protected]</a>
<i class="ai ai-orcid" aria-hidden="true"></i> <a href="https://orcid.org/0000-0003-0530-4305">0000-0003-0530-4305</a>
<i class="fa fa-twitter" aria-hidden="true"></i> <a href="https://twitter.com/essepuntato">@essepuntato</a>
</p>
<p class="sst mtl"><a href="https://www.unibo.it/en/teaching/course-unit-catalogue/course-unit/2024/467045">Computational Thinking and Programming (A.Y. 2024/2025)</a></p>
<p class="ssst"><a href="https://corsi.unibo.it/2cycle/DigitalHumanitiesKnowledge">Second Cycle Degree in Digital Humanities and Digital Knowledge</a></p>
<p class="ssst"><a href="http://www.unibo.it/en">Alma Mater Studiorum - Università di Bologna</a></p>
<p class="license"><a rel="license" href="http://creativecommons.org/licenses/by/4.0/"></a> <a rel="license" href="http://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 International License</a></p>
</div>
</section>

<section>
<h2>Any question about the previous lecture?</h2>
</section>

<section>
<h2>Historic hero: Betty Holberton</h2>
<img class="wm fr mlm" src="img/holberton.jpg" />
<p>She was one of the programmers of the earliest electronic and general-purpose computer, the ENIAC</p>
<p class="fragment">She was involved in the development of several programming languages, such as COBOL and FORTRAN</p>
<p class="fragment">She was the creator of the first statistical analysis tool</p>
<p class="fragment">A huge part of her work about the development of algorithms for sorting the elements in a list</p>
</section>

<section>
<h2>Why sorting is important</h2>
<p>Sorting things is expensive, in particular if you have to order billions of items</p>
<p>However, having such items sorted is crucial for several <span class="fragment highlight-red">additional</span> kinds of tasks that we can perform</p>
<p class="fragment">Library: books are clustered according to Dewey classification, and each cluster contains books ordered according to the authors' name and the book title</p>
<p class="fragment">In this way a librarian can find a requested title avoiding to look all the billion books available one by one, thus saving a huge amount of time</p>
</section>

<section>
<h2 class="bbt">Addressing computational problems</h2>
<p>Problem-solving: the activity of <span class="fragment highlight-red">creating an algorithm</span> for solving some given <span class="fragment highlight-red">computational problem</span>, e.g. ordering alphabetically all the books in a library</p>
<div class="fragment">
<p>Categories of problem-solving methods:</p>
<ul>
<li><p class="fragment highlight-red">brute-force</p></li>
<li><p>divide and conquer</p></li>
<li><p>dynamic programming</p></li>
<li><p>backtracking</p></li>
<li><p>greedy</p></li>
<li><p>...</p></li>
</ul>
</div>
</section>

<section>
<h2>Brute-force approach</h2>
<p>Brute-force algorithm: a process that reaches the perfect solution of a problem by analysing <span class="fragment highlight-red">all</span> the possible candidates that may provide a solution to a certain computational problem, and then <span class="fragment highlight-red">check</span> if each candidate solves the problem question</p>
<p class="fragment">Advantages: simple, it finds a solution always</p>
<p class="fragment">Disadvantages: costly for large inputs</p>
<p class="fragment">Suggestion: use brute-force algorithms when the problem size is small</p>
</section>

<section>
<h2>Big solution spaces</h2>
<img class="fragment wm fr mlm" src="img/go.jpg" data-fragment-index="1" />
<p>Abstract strategy board games are computational problems that have a quite huge solution space</p>
<p class="fragment" data-fragment-index="1">Develop a brute-force algorithm which is able to play appropriately Go means to consider all the possible legal moves that are available on the board</p>
<p class="fragment sst">Number of all the possible legal moves in Go: 208168199381979984699478633344862770286522453884530548425639456820927419612738015378525648451698519643907259916015628128546089888314427129715319317557736620397247064840935</p>
<p class="fragment">Avoid brute-force for these kinds of problems</p>
</section>

<section>
<h2>Iteration</h2>
<p>The usual way for solving computational problems by means of a brute-force approach is to <span class="fragment highlight-red">iterate</span> over a certain input or a block of instructions several times</p>
<div class="fragment">
<p class="mbs">Foreach loop</p>
<pre class="mtn"><code class="python">for item in &lt;collection>:
# do something using the current item</code></pre>
</div>
<div class="fragment">
<p class="mbs">While loop</p>
<pre class="mtn"><code class="python">while &lt;condition>:
# do something until the condition is true</code></pre>
</div>
</section>

<section>
<h2>Foreach: an example</h2>
<pre><code>def stack_from_list(input_list):
output_stack = deque()

for item in input_list:
output_stack.append(item)
​
return output_stack</code></pre>

<div class="fragment" data-fragment-index="1">

<p class="fl">
<code>input_list = </code>
<span class="cell fragment highlight-red" data-fragment-index="2">12</span>
<span class="cell fragment highlight-red" data-fragment-index="4">15</span>
<span class="cell fragment highlight-red" data-fragment-index="6">83</span>
<code class="fragment mll" data-fragment-index="1">output_stack =</code>
</p>

<div style="margin-left: 85%">
<div><span class="cell fragment" data-fragment-index="7">83</span></div>
<div><span class="cell fragment" data-fragment-index="5">15</span></div>
<div><span class="cell fragment" data-fragment-index="3">12</span></div>
</div>
</div>
</section>

<section>
<h2>While: an example</h2>
<pre><code>def run_forever():
value = 0
​
while value >= 0:
value = value + 1</code></pre>
<p class="fragment" data-fragment-index="0">
<code>value = </code>
<span class="fragment" data-fragment-index="1"><span class="fragment fade-out" data-fragment-index="2">0</span></span>
<span class="fragment" data-fragment-index="2"><span class="fragment fade-out" data-fragment-index="3">1</span></span>
<span class="fragment" data-fragment-index="3"><span class="fragment fade-out" data-fragment-index="4">2</span></span>
<span class="fragment" data-fragment-index="4"><span class="fragment fade-out" data-fragment-index="5">3</span></span>
<span class="fragment" data-fragment-index="5"><span class="fragment fade-out" data-fragment-index="6">4</span></span>
<span class="fragment" data-fragment-index="6">...</span>
</p>
</section>

<section>
<h2>Linear search: description</h2>
<p>Computational problem: find the position of the first occurrence of a value within a list</p>
<img class="wm fr fragment" src="img/position.png" data-fragment-index="2" />
<ol class="fragment wl" data-fragment-index="1">
<li><p>Iterate over the items in the input list</p></li>
<li><p>Check if each of them is equal to the value we are looking for</p></li>
<li><p>Once the value has been found, its position in the list is then returned</p></li>
<li><p>If the value is not contained in the list, no position is returned at all</p></li>
</ol>
</section>

<section>
<h2>Ancillary objects and algorithms</h2>
<p>Tuple: sequence of values, specified in a precise order - they are different from lists since they cannot be modified</p>
<pre><code>my_tuple = (1, "a", 2, ...)</code></pre>
<div class="fragment">
<p>The function <code>enumerate(&lt;list>)</code> returns an enumeration (i.e. a kind of list) of tuples, with two elements each: the first element is the position of the item in consideration in the list, while the second element is the item itself</p>
<pre><code class="python">my_list = list()
my_list.append("a")
my_list.append("b")
my_list.append("c")
enumerate(my_list)
# it will return the following enumeration of tuples:
# enumerate([(0, "a"), (1, "b"), (2, "c")])</code></pre>
</div>
</section>

<section>
<h2>Decoupling tuples in foreach</h2>
<p>Python allows us to decouple the items in a tuple by specifying names for each item with variables created in the <code>for</code> statement on-the-fly</p>
<p>For instance,<br /><code>for position, item in enumerate(my_list)</code><br />will assign (the number in the following list refers to the particular iteration of the foreach loop):</p>
<ol class="fragment">
<li><p><code>position = 0</code> and <code>item = "a"</code></p></li>
<li class="fragment"><p><code>position = 1</code> and <code>item = "b"</code></p></li>
<li class="fragment"><p><code>position = 2</code> and <code>item = "c"</code></p></li>
</ol>
</section>

<section>
<h2>Linear search: algorithm</h2>
<pre><code>def linear_search(input_list, value_to_search):​
for ​position, item in enumerate(input_list):
if item == value_to_search:
return position</code></pre>
<p>In Python, <code>None</code> (that means <em>nothing</em>) is returned if no <code>return</code> statement is executed</p>
</section>

<section>
<section data-transition="slide-in fade-out">
<h2>Insertion sort: description</h2>
<p>Computational problem: sort all the items in a given list</p>
<p class="tc fragment"><img src="img/insertion-01.png" /></p>
</section>

<section data-transition="fade-in">
<h2>Insertion sort: description</h2>
<p>Computational problem: sort all the items in a given list</p>
<p class="tc"><img src="img/insertion-02.png" /></p>
</section>

<section data-transition="fade-in">
<h2>Insertion sort: description</h2>
<p>Computational problem: sort all the items in a given list</p>
<p class="tc"><img src="img/insertion-03.png" /></p>
</section>

<section data-transition="fade-in">
<h2>Insertion sort: description</h2>
<p>Computational problem: sort all the items in a given list</p>
<p class="tc"><img src="img/insertion-04.png" /></p>
</section>

<section data-transition="fade-in">
<h2>Insertion sort: description</h2>
<p>Computational problem: sort all the items in a given list</p>
<p class="tc"><img src="img/insertion-05.png" /></p>
</section>

<section data-transition="fade-in">
<h2>Insertion sort: description</h2>
<p>Computational problem: sort all the items in a given list</p>
<p class="tc"><img src="img/insertion-06.png" /></p>
</section>
</section>

<section>
<h2>Useful functions</h2>
<p class="mbs"><code>range(&lt;stop_number>)</code> returns the range (i.e. a kind of list) of all numbers from 0 to the one preceding the stop number</p>
<p class="mtn sst">E.g.: <code>range(3)</code> returns <code>range([0, 1, 2])</code>, while <code>range(0)</code> returns an empty range</p>
<div class="fragment">
<p class="mbs"><code>reversed(&lt;input_list>)</code> returns an iterator of the list as if all the elements are sorted in the opposite order</p>
<p class="mtn sst">E.g.: considering <code>my_list = list([0, 1, 2])</code>, <code>reversed(my_list)</code> returns <code>iterator([2, 1, 0])</code></p>
</div>
</section>

<section>
<h2>Get and insert items by position</h2>
<p class="mbs"><code>&lt;list>[&lt;position>]</code> returns the item in the list at that particular position</p>
<p class="mtn sst">E.g.: considering <code>my_list = list(["a", "b", "c"])</code>, <code>my_list[1]</code> returns <code>"b"</code></p>
<div class="fragment">
<p>The method <code>&lt;list>.insert(&lt;position>, &lt;item>)</code> puts &lt;item> in the position specified, and it shifts all the following elements</p>
<p class="mtn sst">E.g.: <code>my_list.insert(1, "d")</code> modifies <code>my_list</code> as <code>list(["a", "d", "b", "c"])</code></p>
</div>
</section>

<section>
<h2>Insertion sort: algorithm</h2>
<pre><code class="python">def insertion_sort(input_list):
result = list()

for item in input_list:
insert_position = len(result)

for prev_position in reversed(range(insert_position)):
if item < result[prev_position]:
insert_position = prev_position

result.insert(insert_position, item)

return result</code></pre>
</section>

<section>
<h2>Additional readings </h2>
<p>From <a href="https://www.digitalocean.com/community/books/digitalocean-ebook-how-to-code-in-python">How To Code in Python</a>:</p>
<ul>
<li>
Chapter "How To Construct While Loops"<br />
<small>All content</small>
</li>
<li>
Chapter "How To Construct For Loops"<br />
<small>All content</small>
</li>
<li>
Chapter "Understanding Tuples"<br />
<small>All content</small>
</li>
<li>
Chapter "Understanding Lists"<br />
<small>Section "Constructing a List with List Items"</small>
</li>
<li>
Chapter "How To Use List Methods"<br />
<small>Section "list.insert()</small>
</li>
</ul>
</section>


<section class="title_slide">
<h2>
END
<span class="subtitle">Brute-force algorithms</span>
</h2>
<div class="author">
<p><a href="https://www.unibo.it/sitoweb/silvio.peroni/en">Silvio Peroni</a></p>
<p class="contact">
<i class="fa fa-envelope" aria-hidden="true"></i> <a href="mailto:[email protected]">[email protected]</a>
<i class="ai ai-orcid" aria-hidden="true"></i> <a href="https://orcid.org/0000-0003-0530-4305">0000-0003-0530-4305</a>
<i class="fa fa-twitter" aria-hidden="true"></i> <a href="https://twitter.com/essepuntato">@essepuntato</a>
</p>
<p class="sst mtl"><a href="https://www.unibo.it/en/teaching/course-unit-catalogue/course-unit/2024/467045">Computational Thinking and Programming (A.Y. 2024/2025)</a></p>
<p class="ssst"><a href="https://corsi.unibo.it/2cycle/DigitalHumanitiesKnowledge">Second Cycle Degree in Digital Humanities and Digital Knowledge</a></p>
<p class="ssst"><a href="http://www.unibo.it/en">Alma Mater Studiorum - Università di Bologna</a></p>
</div>
</section>
</div>
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