Starting from:
$35
"The Most Probable Song Title" Solved
For this lab you will be using Ruby. Although Ruby is Hybrid language which combines Scripting, Imperative, Functional, and Object-Oriented concepts, we will be focusing simply on the Scriptin and Imperative elements. Thus, solutions utilizing Functional or OO capabilities will be heavily penalized.
You can install ruby using instructions found at the following sites:
Windows
Mac
Linux
Concepts we will explore as a part of this Lab:
Regular Expression - See this tutorial and this too
Ruby - See this tutorial
Procedural Languages
Step -1: Fork and Clone this
Repository
1. Using the Fork button above fork your own version of this repository.
2. On your system, use your installation of Git to clone your fork of this repo on your local
machine.
3. Once you have the repository cloned, you can continue on.
Step 0: Getting everything ready
1. Install Bundler
gem install bundler
2. Install project dependencies (from the project root directory)
bundler install --binstubs
Dataset
This lab will make use of a dataset containing a million song titles. This dataset is used in various
machine learning experiments and is provided by the Laboratory for the Recognition and
Organization of Speech and Audio at Columbia University. I have added this dataset to the
repository under the name unique_tracks.txt
In addition, I have created a subset of this dataset containing only song titles that begin with the
letter "A". We will use this file for debugging and testing purposes. This can be found in the file
a_tracks.txt .
File Templates
There are four files of concern in the project directory:
ruby_lab.rb - This is the ruby template in which you will add code to complete this
assignment. You are given some code, do not remove this code unless you are sure of what
you are doing. If the tests do not pass due to your modifications, you will lose credit.
questions.txt - This is the file in which you will answer identified questions as part of the lab.
a_tracks.txt - A small testing data set which is a subset (only tracks with titles starting with
"A") derived from the next file.
unique_tracks.txt - The million record data set which we will use for the lab.
There are some other files:
spec/*spec.rb - These are test files used by RSpec to evaluate your code.
.rspec - This indicates to RSpec that this project can be tested
Gemfile - provides the specicification of dependencies for this project
README.md - this markdown file
This program takes as input the dataset file. For example, I execute the program at the command
line as follows:
$ ruby ruby_lab.rb unique_tracks.txt
This initial template gives code to loop through each line of the file and prints out the line. You
probably will not want to keep this line. Remember you use Ctrl+C or Cmd+C to cancel the
execution of the program.
Pre-processing
Step 1: Extract song title
Each line contains a track id, song id, artist name, and the song title, such as:
TRWRJSX12903CD8446<SEPSOBSFBU12AB018DBE1<SEPFrank Sinatra<SEPEverything Happens To Me
You are only concerned with the last field, the song title. As your first task, you will write a regular
expression that extracts the song title and stores it as the variable title . You will discard all
other information.
You may find this site useful in debugging your regular expression: https://regex101.com/. It allows
you to test your regular expressions on a block of text that your provide.
Step 2: Eliminate superfluous text
The song title, however, is quite noisy, often containing additional information beyond the song
title. Consider this example:
Strangers in the Night (Remastered Album Version) [The Frank Sinatra Collection]
You need to perform some pre-processing in order to clean up the song titles. You will write a
series of regular expressions that match a block of text and replace it with nothing.
Begin by writing a regular expression that matches a left parenthesis and any text that follows it.
You need not match the right parenthesis explicitly. Replace the parenthesis and all text that
follows it with nothing.
In the above Sinatra example, the modified title becomes Strangers In The Night .
Repeat this for patterns beginning with the left bracket, the left curly brace, and all the other
characters listed below:
( [ { \ / _ - : " ` + = * feat.
Note that the above lists the left quote (on the tilde key above tab) and not the apostrophe (located
left of the enter key). This is a very important distinction. We do no want to omit the apostrophe as
it allows contractions.
Many of these characters have special meanings in Ruby. Make sure you properly escape
symbols when necessary. Failing to escape characters properly will be the most common mistake
made in this lab.
The last one listed above is an abbreviation feat. -- short for featuring and followed by artist
information you do not need to retain. For example, Sunbeam feat. Vishal Vaid becomes
Sunbeam .
In most cases, these symbols indicate additional information that need not concern us for this
exercise. The above steps will very occasionally corrupt a valid song title that actually contains, for
example, parentheses in the song title. Do not worry about these infrequent cases and uniformly
carry out the procedure listed above. These steps will catch and fix the vast majority of
irregularities in the song titles.
Step 3: Eliminate punctuation
Next, find and delete the following typical punctuation marks:
? ¿ ! ¡ . ; & @ % # |
Unlike before, delete only the symbol itself and leave all of the text that follows. Be sure to do a
'global' match in order to replace all instances of the punctuation mark. Be careful to match the
period itself as the symbol "." has a special meaning in regular expressions. This is true for many
of the symbols above. Again, refer to a list of escape characters specific to the language you
selected.
Step 4: Filter out non-English characters
Lastly, ignore all song titles that contain a non-English character (e.g., á, ı̀, ö, etc.). (Hint: it may be
easier to match titles that contain only English characters than to match titles that contain non-
English characters). I define "English characters" to include the word meta-character definition
(typically \w and \s in most languages) as well as the apostrophe character. This process will
allow a few non-English song titles to creep through (e.g., amore mio), but will eliminate the
majority of non-English titles.
Step 5: Set to lowercase
Convert all words in the sentence to lowercase. Each of these languages has a special function to
do this for you.
Self-Check
In the a_tracks dataset, after all filtering steps, I find 52,760 valid song titles.
N.B.: If you are close to my number (within 10's), that is sufficient. If you are way off (i.e., 100+),
you should double check your regular expressions.
This check can be performed using the following command:
On Mac or Linux:
rspec spec/self_check_1_spec.rb
On Windows:
rspec spec\self_check_1_spec.rb
Bi-gram Counts
A bigram is a sequence of two adjacent words in a text. The frequency distribution of bigrams in
text(s) is commonly used in statistical natural language processing (see
http://en.wikipedia.org/wiki/Bigram). Across this corpus of one million song titles, you will count all
the bigram words.
First, you need to split the title string into individual words. Next, you should use one or more data
structures to keep track of these word pair counts. That is, for every word, you must keep track of
the count for each word that follows it. I strongly recommend you design your data structure for
fast retrieval. Put some thought into which data structure to choose. Once you have decided, you
can compare your choice to mine.
Self-Check
After you build and populate your bigram data structure, you can check yourself.
In the a_tracks dataset:
This check can be performed using the following command:
On Mac or Linux:
rspec spec/self_check_2_spec.rb
On Windows:
rspec spec\self_check_2_spec.rb
The most common word to follow "happy" is "now"
The most common word to follow "sad" is "love"
The most common word to follow "love" is "song"
There are 80 distinct words that follow the word "love".
The word "song" follows "love" 33 times.
Building a Song Title
Now you are going to build a probabilistic song title. First begin by creating a function "most
common word" mcw() . This function will take in one argument, some word, and returns the word
that most often followed that word in the dataset. If you find a tie, randomly select one value. For
example, the line puts mcw("computer") should give you your answer to Question 4.
Now you are going to use this function to string together a song title. Beginning with a given
starting word, write an iterative structure that strings together words that most commonly follow
each other in the dataset. Continue until a word does not have a successive word in the dataset,
or the count of words in your title reaches 20.
Lab Questions
Use your data structure(s) on the unique_tracks dataset to answer these and all subsequent
Lab Questions.
To answer these questions execute the following command (in the terminal) from the root directory
of your project:
On Mac or Linux
rspec spec/lab_quest_1_5_spec.rb -o lab_quest_1_5_output.txt
On Windows:
rspec spec\lab_quest_1_5_spec.rb -o lab_quest_1_5_output.txt
1. Which word most often follows the word "happy"?
2. Which word most often follows the word "sad"?
3. How many different (unique) words follow the word "computer"?
4. Which word most often follows the word "computer"?
5. How many times does this word follow "computer"?
User Control
Now add loop that repeatedly queries the user for a starting word until they choose to quit. I
started it for you in the template. Your program will ask:
Enter a word [Enter 'q' to quit]:
For each word entered, use your code above to create a song title of 20 words (or less). Print out
your newly designed song title. Repeat, querying the user for a new word.
Self-Check
For the a_tracks dataset:
This check can be performed using the following command:
On Mac or Linux:
rspec spec/self_check_3_spec.rb
On Windows:
rspec spec\self_check_3_spec.rb
Using the seed word "happy", you should get the title: happy now the world of the world
of the world of the world of the world of the world of
Using the seed word "sad", you should get the title: sad love song for you ready for you
ready for you ready for you ready for you ready for you ready
Using the seed word "computer", you should get the title: computer because no song titles
in a_tracks contain the word "computer"
Lab Questions
To answer these questions execute the following command (in the terminal) from the root directory
of your project, for questions 6-9. Question 10 should be answered in the questions.txt file:
On Mac or Linux
rspec spec/lab_quest_6_9_spec.rb -o lab_quest_6_9_output.txt
On Windows:
rspec spec\lab_quest_6_9_spec.rb -o lab_quest_6_9_output.txt
1. Using the starting word "happy", what song title do you get?
2. Using the starting word "sad", what song title do you get?
3. Using the starting word "hey", what song title do you get?
4. Using the starting word "little", what song title do you get?
5. Try a few other words. What problem(s) do you see? Which phrase do you most often find
recurring in these titles?
Stop Words
Next try to fix the aforementioned problem(s) you observed in Question 10. In NLP, stop words are
common words that are often filtered out, such as common function words and articles. Before
taking your bigram counts, filter out the following common stop words from the song title:
a, an, and, by, for, from, in, of, on, or, out, the, to, with
Lab Questions
To answer these questions execute the following command (in the terminal) from the root directory
of your project, for questions 11-13. Questions 14 and 15 should be answered the qustions.txt
file.:
On Mac or Linux
rspec spec/lab_quest_11_13_spec.rb -o lab_quest_11_13_output.txt
On Windows:
rspec spec\lab_quest_11_13_spec.rb -o lab_quest_11_13_output.txt
1. Using the starting word "amore", what song title do you get?
2. Using the starting word "love", what song title do you get?
3. Using the starting word "little", what song title do you get?
4. Explain why so many of the titles devolve into repeating patterns.
5. Try several words. Find a song title that terminates in less than 20 words. Could you find one?
If so, which song title did you find? If not, why not?
Last Step
Implement a "fix" for the problematic phenomenon you observed in Question 6. If you have
successfully solved these problems, you can remove the restriction of 20 words maximum in the
song title. (Hint: If it goes boom, then you have not solved the problem)
Lab Questions
Answere the following questions Questions 16 through 20 in the questions.txt file.:
1. Describe in one or two paragraphs your extension and how it fixed the repeating phrase/word
problem.
2. Using the starting word "montana", what song title do you get?
3. Using the starting word "bob", what song title do you get?
4. Using the starting word "bob" again, do you get the same title? If no, what do you get? Try it
a third time. Explain why the title might differ each time.
5. Share your favorite song title that you have found.
Troubleshooting
This lab requires an independent study of the Ruby language. You are encouraged to use any web
tutorials and resources to learn this language. Given the size of the class, I will not be able to
debug your code for you. Please do not send panicked emails requesting I fix your bug for
you. Allow yourself plenty of time, and use patience, perseverance, and the internet to
debug your code.
Lab Questions
The following questions are for feedback and evaluation purposes. Points are awarded for any
sincere answer.
These questions should be answered in the questions.txt file.
1. Name something you like about Ruby. Explain.
2. Name something you dislike about Ruby. Explain.
3. Did you enjoy this lab? Which aspects did you like and/or dislike?
4. Approximately how many hours did you spend on this lab?
5. Do you think you would use Ruby again? For which type(s) of project(s)?
Grading
With the exception of questions 10, 14, 15, 16, 19, and 20 questions 1-20 are automatically
graded by passing the associated tests. This is all or nothing, either you passed the tests or not.
The remaining questions will be graded based on your answers and may receive partial credit.
Questions 21 - 25 will be awarded full credit as long as there is a sincere and appropriate answer.
Questions 1-20 - 2 points each
Questions 21-25 - 1 points each
Comments and Code Style - 5 points
Submission
Each student will complete and submit this assignment individually. Do not consult with others.
However, you are encouraged to use the internet to learn any aspect of Ruby you need to
complete the assignment, but not to answer the questions asked in this lab.
Comment your program heavily. Intelligent comments and a clean, readable formatting of your
code accounts for 20% of your grade.
Save the final version of your program and construct a zip file containing ONLY the following
items:
ruby_lab.rb
lab_quest_1_5_output.txt
lab_quest_6_9_output.txt
lab_quest_11_13_output.txt
questions.txt
Note, I will only accept plain text files for your answers. The submission of PDF,
Word, Images, or anything other format except plain text will recevie zero credit.
You can install ruby using instructions found at the following sites:
Windows
Mac
Linux
Concepts we will explore as a part of this Lab:
Regular Expression - See this tutorial and this too
Ruby - See this tutorial
Procedural Languages
Step -1: Fork and Clone this
Repository
1. Using the Fork button above fork your own version of this repository.
2. On your system, use your installation of Git to clone your fork of this repo on your local
machine.
3. Once you have the repository cloned, you can continue on.
Step 0: Getting everything ready
1. Install Bundler
gem install bundler
2. Install project dependencies (from the project root directory)
bundler install --binstubs
Dataset
This lab will make use of a dataset containing a million song titles. This dataset is used in various
machine learning experiments and is provided by the Laboratory for the Recognition and
Organization of Speech and Audio at Columbia University. I have added this dataset to the
repository under the name unique_tracks.txt
In addition, I have created a subset of this dataset containing only song titles that begin with the
letter "A". We will use this file for debugging and testing purposes. This can be found in the file
a_tracks.txt .
File Templates
There are four files of concern in the project directory:
ruby_lab.rb - This is the ruby template in which you will add code to complete this
assignment. You are given some code, do not remove this code unless you are sure of what
you are doing. If the tests do not pass due to your modifications, you will lose credit.
questions.txt - This is the file in which you will answer identified questions as part of the lab.
a_tracks.txt - A small testing data set which is a subset (only tracks with titles starting with
"A") derived from the next file.
unique_tracks.txt - The million record data set which we will use for the lab.
There are some other files:
spec/*spec.rb - These are test files used by RSpec to evaluate your code.
.rspec - This indicates to RSpec that this project can be tested
Gemfile - provides the specicification of dependencies for this project
README.md - this markdown file
This program takes as input the dataset file. For example, I execute the program at the command
line as follows:
$ ruby ruby_lab.rb unique_tracks.txt
This initial template gives code to loop through each line of the file and prints out the line. You
probably will not want to keep this line. Remember you use Ctrl+C or Cmd+C to cancel the
execution of the program.
Pre-processing
Step 1: Extract song title
Each line contains a track id, song id, artist name, and the song title, such as:
TRWRJSX12903CD8446<SEPSOBSFBU12AB018DBE1<SEPFrank Sinatra<SEPEverything Happens To Me
You are only concerned with the last field, the song title. As your first task, you will write a regular
expression that extracts the song title and stores it as the variable title . You will discard all
other information.
You may find this site useful in debugging your regular expression: https://regex101.com/. It allows
you to test your regular expressions on a block of text that your provide.
Step 2: Eliminate superfluous text
The song title, however, is quite noisy, often containing additional information beyond the song
title. Consider this example:
Strangers in the Night (Remastered Album Version) [The Frank Sinatra Collection]
You need to perform some pre-processing in order to clean up the song titles. You will write a
series of regular expressions that match a block of text and replace it with nothing.
Begin by writing a regular expression that matches a left parenthesis and any text that follows it.
You need not match the right parenthesis explicitly. Replace the parenthesis and all text that
follows it with nothing.
In the above Sinatra example, the modified title becomes Strangers In The Night .
Repeat this for patterns beginning with the left bracket, the left curly brace, and all the other
characters listed below:
( [ { \ / _ - : " ` + = * feat.
Note that the above lists the left quote (on the tilde key above tab) and not the apostrophe (located
left of the enter key). This is a very important distinction. We do no want to omit the apostrophe as
it allows contractions.
Many of these characters have special meanings in Ruby. Make sure you properly escape
symbols when necessary. Failing to escape characters properly will be the most common mistake
made in this lab.
The last one listed above is an abbreviation feat. -- short for featuring and followed by artist
information you do not need to retain. For example, Sunbeam feat. Vishal Vaid becomes
Sunbeam .
In most cases, these symbols indicate additional information that need not concern us for this
exercise. The above steps will very occasionally corrupt a valid song title that actually contains, for
example, parentheses in the song title. Do not worry about these infrequent cases and uniformly
carry out the procedure listed above. These steps will catch and fix the vast majority of
irregularities in the song titles.
Step 3: Eliminate punctuation
Next, find and delete the following typical punctuation marks:
? ¿ ! ¡ . ; & @ % # |
Unlike before, delete only the symbol itself and leave all of the text that follows. Be sure to do a
'global' match in order to replace all instances of the punctuation mark. Be careful to match the
period itself as the symbol "." has a special meaning in regular expressions. This is true for many
of the symbols above. Again, refer to a list of escape characters specific to the language you
selected.
Step 4: Filter out non-English characters
Lastly, ignore all song titles that contain a non-English character (e.g., á, ı̀, ö, etc.). (Hint: it may be
easier to match titles that contain only English characters than to match titles that contain non-
English characters). I define "English characters" to include the word meta-character definition
(typically \w and \s in most languages) as well as the apostrophe character. This process will
allow a few non-English song titles to creep through (e.g., amore mio), but will eliminate the
majority of non-English titles.
Step 5: Set to lowercase
Convert all words in the sentence to lowercase. Each of these languages has a special function to
do this for you.
Self-Check
In the a_tracks dataset, after all filtering steps, I find 52,760 valid song titles.
N.B.: If you are close to my number (within 10's), that is sufficient. If you are way off (i.e., 100+),
you should double check your regular expressions.
This check can be performed using the following command:
On Mac or Linux:
rspec spec/self_check_1_spec.rb
On Windows:
rspec spec\self_check_1_spec.rb
Bi-gram Counts
A bigram is a sequence of two adjacent words in a text. The frequency distribution of bigrams in
text(s) is commonly used in statistical natural language processing (see
http://en.wikipedia.org/wiki/Bigram). Across this corpus of one million song titles, you will count all
the bigram words.
First, you need to split the title string into individual words. Next, you should use one or more data
structures to keep track of these word pair counts. That is, for every word, you must keep track of
the count for each word that follows it. I strongly recommend you design your data structure for
fast retrieval. Put some thought into which data structure to choose. Once you have decided, you
can compare your choice to mine.
Self-Check
After you build and populate your bigram data structure, you can check yourself.
In the a_tracks dataset:
This check can be performed using the following command:
On Mac or Linux:
rspec spec/self_check_2_spec.rb
On Windows:
rspec spec\self_check_2_spec.rb
The most common word to follow "happy" is "now"
The most common word to follow "sad" is "love"
The most common word to follow "love" is "song"
There are 80 distinct words that follow the word "love".
The word "song" follows "love" 33 times.
Building a Song Title
Now you are going to build a probabilistic song title. First begin by creating a function "most
common word" mcw() . This function will take in one argument, some word, and returns the word
that most often followed that word in the dataset. If you find a tie, randomly select one value. For
example, the line puts mcw("computer") should give you your answer to Question 4.
Now you are going to use this function to string together a song title. Beginning with a given
starting word, write an iterative structure that strings together words that most commonly follow
each other in the dataset. Continue until a word does not have a successive word in the dataset,
or the count of words in your title reaches 20.
Lab Questions
Use your data structure(s) on the unique_tracks dataset to answer these and all subsequent
Lab Questions.
To answer these questions execute the following command (in the terminal) from the root directory
of your project:
On Mac or Linux
rspec spec/lab_quest_1_5_spec.rb -o lab_quest_1_5_output.txt
On Windows:
rspec spec\lab_quest_1_5_spec.rb -o lab_quest_1_5_output.txt
1. Which word most often follows the word "happy"?
2. Which word most often follows the word "sad"?
3. How many different (unique) words follow the word "computer"?
4. Which word most often follows the word "computer"?
5. How many times does this word follow "computer"?
User Control
Now add loop that repeatedly queries the user for a starting word until they choose to quit. I
started it for you in the template. Your program will ask:
Enter a word [Enter 'q' to quit]:
For each word entered, use your code above to create a song title of 20 words (or less). Print out
your newly designed song title. Repeat, querying the user for a new word.
Self-Check
For the a_tracks dataset:
This check can be performed using the following command:
On Mac or Linux:
rspec spec/self_check_3_spec.rb
On Windows:
rspec spec\self_check_3_spec.rb
Using the seed word "happy", you should get the title: happy now the world of the world
of the world of the world of the world of the world of
Using the seed word "sad", you should get the title: sad love song for you ready for you
ready for you ready for you ready for you ready for you ready
Using the seed word "computer", you should get the title: computer because no song titles
in a_tracks contain the word "computer"
Lab Questions
To answer these questions execute the following command (in the terminal) from the root directory
of your project, for questions 6-9. Question 10 should be answered in the questions.txt file:
On Mac or Linux
rspec spec/lab_quest_6_9_spec.rb -o lab_quest_6_9_output.txt
On Windows:
rspec spec\lab_quest_6_9_spec.rb -o lab_quest_6_9_output.txt
1. Using the starting word "happy", what song title do you get?
2. Using the starting word "sad", what song title do you get?
3. Using the starting word "hey", what song title do you get?
4. Using the starting word "little", what song title do you get?
5. Try a few other words. What problem(s) do you see? Which phrase do you most often find
recurring in these titles?
Stop Words
Next try to fix the aforementioned problem(s) you observed in Question 10. In NLP, stop words are
common words that are often filtered out, such as common function words and articles. Before
taking your bigram counts, filter out the following common stop words from the song title:
a, an, and, by, for, from, in, of, on, or, out, the, to, with
Lab Questions
To answer these questions execute the following command (in the terminal) from the root directory
of your project, for questions 11-13. Questions 14 and 15 should be answered the qustions.txt
file.:
On Mac or Linux
rspec spec/lab_quest_11_13_spec.rb -o lab_quest_11_13_output.txt
On Windows:
rspec spec\lab_quest_11_13_spec.rb -o lab_quest_11_13_output.txt
1. Using the starting word "amore", what song title do you get?
2. Using the starting word "love", what song title do you get?
3. Using the starting word "little", what song title do you get?
4. Explain why so many of the titles devolve into repeating patterns.
5. Try several words. Find a song title that terminates in less than 20 words. Could you find one?
If so, which song title did you find? If not, why not?
Last Step
Implement a "fix" for the problematic phenomenon you observed in Question 6. If you have
successfully solved these problems, you can remove the restriction of 20 words maximum in the
song title. (Hint: If it goes boom, then you have not solved the problem)
Lab Questions
Answere the following questions Questions 16 through 20 in the questions.txt file.:
1. Describe in one or two paragraphs your extension and how it fixed the repeating phrase/word
problem.
2. Using the starting word "montana", what song title do you get?
3. Using the starting word "bob", what song title do you get?
4. Using the starting word "bob" again, do you get the same title? If no, what do you get? Try it
a third time. Explain why the title might differ each time.
5. Share your favorite song title that you have found.
Troubleshooting
This lab requires an independent study of the Ruby language. You are encouraged to use any web
tutorials and resources to learn this language. Given the size of the class, I will not be able to
debug your code for you. Please do not send panicked emails requesting I fix your bug for
you. Allow yourself plenty of time, and use patience, perseverance, and the internet to
debug your code.
Lab Questions
The following questions are for feedback and evaluation purposes. Points are awarded for any
sincere answer.
These questions should be answered in the questions.txt file.
1. Name something you like about Ruby. Explain.
2. Name something you dislike about Ruby. Explain.
3. Did you enjoy this lab? Which aspects did you like and/or dislike?
4. Approximately how many hours did you spend on this lab?
5. Do you think you would use Ruby again? For which type(s) of project(s)?
Grading
With the exception of questions 10, 14, 15, 16, 19, and 20 questions 1-20 are automatically
graded by passing the associated tests. This is all or nothing, either you passed the tests or not.
The remaining questions will be graded based on your answers and may receive partial credit.
Questions 21 - 25 will be awarded full credit as long as there is a sincere and appropriate answer.
Questions 1-20 - 2 points each
Questions 21-25 - 1 points each
Comments and Code Style - 5 points
Submission
Each student will complete and submit this assignment individually. Do not consult with others.
However, you are encouraged to use the internet to learn any aspect of Ruby you need to
complete the assignment, but not to answer the questions asked in this lab.
Comment your program heavily. Intelligent comments and a clean, readable formatting of your
code accounts for 20% of your grade.
Save the final version of your program and construct a zip file containing ONLY the following
items:
ruby_lab.rb
lab_quest_1_5_output.txt
lab_quest_6_9_output.txt
lab_quest_11_13_output.txt
questions.txt
Note, I will only accept plain text files for your answers. The submission of PDF,
Word, Images, or anything other format except plain text will recevie zero credit.
1 file (38.4MB)
