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						ASSIGNMENT DEVOpS

Assignment #1

One of the requirements is to learn adequate scripting and programming to be 
able to solve routine data-related problems. You are expected to learn Linux 
commands, BASH scripting, and Python for systems administration/management.

The following is a sample assignment just to get you off the ground. You must 
set practice projects such as these for yourself and gain confidence.

(1) Inspect the output of the command 'ps -ef'. Use grep to detect if there are
    processes with names starting with 'chrome' and 'firefox'
(2) For each of the process identified in step (1) above, use 'cut' or 
    equivalent command to project its process id.
(3) Kill each of the process selected in step (2) above.
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(4) Each tab in Google Chrome browser is an independent process. Write a shell
    script to terminate the process that corresponds to a particular tab in the
    browser.
(5) Taking 'home' directory as the root, recursively enumerate all files with 
    extensions matching '.pdf' or '.txt' that were created a week ago (or some 
    arbitrary time, for that matter).
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(6) What is the official/documented way to install a new Python module in the
    system?
(7) What purpose does the '/proc' file system in Linux serve? Use your
    imagination and suggest two ideas that may be pretty useful in your own
    case. Could you write a shell script to achieve the same?
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(8) Have you installed both Python 2.7.X and 3.2.X in your machine? How would 
    you set up your computer to have a side-by-side installation of both
    versions of Python (so you can test your programs on both platforms)?
(9) Use a container (virtualization) technology such as OpenVZ (which is pretty
    lightweight) and use separate containers to host different versions of
    Python.
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(10) Use your imagination and originality to grow the list.


Assignment #2.

Retrieve the date and time of all commits, and the corresponding commit (text) 
messages, for each of the following three repositories (aka the population):
    https://github.com/sois/sap-efrei-spring-2016
    https://github.com/sois/moderndatabases-monsoon16
    https://github.com/sois/data-visualization

You may assume that you are working on the (checked-out) local repositories. 
Use simple commands such as 'git log' to collect the required data. You are NOT
expected to use any APIs or external libraries, and such.

Analyze the population data, and answer the following questions:
(1) what is the average length (in number of characters) of commit messages?
(2) What is the average word count in commit messages.
(3) What are the most frequently used words in the commit messages?
(4) Do weekdays witness more commits than weekends? 
(5) Do mid-week days witness more or less commits?
(6) If you do a regression analysis, what inferences would you draw?

(A) You must create a visualization for each ot these question. 
(B) You should be able to check how far the visualizations agree with the 
    statistical inferences.

Assignment #3

Randomly select six or seven computers in the laboratory (including your own 
computer), and copy the browsing history from each of the Web browser installed 
on that machine. (If three Web browsers are installed on a computer, copy the 
browsing history from all three browsers). Make sure that you have at least 
five days worth of browsing history for each machine.

(1) Sort the data according to domain names. Measure interesting parameters and 
    develop an equally interesting visualization.
(2) If you run the same experiment across labs in SOIS, can you draw definitive 
    inferences about the browsing habits or practices of users?
(3) Is there a correlation between domain names and the purpose of the lab?
(4) What graphs would you create to effectively convey this information?


Assignment #4.

Collect the marks obtained by each student of your batch (first semester, 'big 
data and data analysis' program) in all five courses.

(1) What visualization would you propose and create in order to present an 
    overall picture of the academic performance? You must be able to logically 
    argue about the methodical choices you have made.
(2) How would you present the average performance of the batch?
(3) Would you compare your batch's performance with that of, say, the students 
    in the 'embedded systems' program? How would you take into account the 
    difference in the population size?
(4) What inferences would you draw from the performances of students in your 
    batch, across five different courses?