About

This repo contains a bunch of demos related to mining various kinds of information from different data sources (e.g., git repos, GitHub repos, Stack Overflow). These are simple use cases just to demonstrate available options and how to get started.

The demos are prepared by Sarah Nadi and are mainly used in CMPUT 663 at the University of Alberta.

Running the Demos

The repo comes with a Dockerfile that takes care of using the correct version of python and setting up dependencies.

First, clone this repo recursively to also clone the submodule:

git clone git@github.com:snadi/MSRDemos.git --recurse-submodules

To build the Docker image (this will take a bit of time):

docker build --tag=msrdemo:f21 .

To run the docker image:

docker run --name MSRDemo -it --rm msrdemo:f21 /bin/sh

All instructions below are based on running from within the Docker image.

Alternatively, you can set up a Python virtual environment and install the dependencies there.

Mining git Repositories

Creating your own scripts for mining git

git provides many commands for exploring the history. You can simply write custom scripts that execute these commands and parse the output.

• For example, go to the elasticsearch repo in repos/ and explore the history using the following git log commands:

git log -10 -p --format=fuller --no-merges
git log -10 -p --format=fuller --no-merges -- '*.gradle'
git log -10 -p --format=fuller --no-merges -- '*.java'

The first one lists the last 10 commits that are not merge commits. The second one lists the last 10 commits that have modified gradle files, while the last one lists the last 10 commits that have modified java files. You can see a structure for how each commit is displayed and you can process that text yourself.

You probably never have to go that route unless you have something very specific to do that current git processing libraries can't support.

Using GitPython

• See http://gitpython.readthedocs.io/en/stable/index.html for complete documentation

• Check out this sample simple script for finding merge conflicts in a repo's history. The criteria here is finding commits with two parents with the word "conflict" in their commit message. Note that this is a simplified crtieria and might miss cases with edited commit messages. The script prints the 5 most recent merge conflicts.

• Running this:

/msrdemo# cd repos/elasticsearch/
/msrdemo/repos/elasticsearch# python ../../scripts/FindMergeConflicts.py 

You should see this output:

09056ed3229ccf42ec006eae65b5941c75452ec4 Thu May 27 06:16:19 2021
4528e780c48ada91fd452b9c51dc1a37772c5f07 Wed May 12 12:50:26 2021
3245e78b780c2b7ee00a2a031582824a79c2ea0a Sat May 19 11:38:17 2018
a5be4149a3ca867f8bb239a8e2a62751b904a392 Thu May 10 17:04:08 2018
db14717098e9e50751654f0f45a0c5cc5441a346 Fri May  4 13:40:57 2018

Take any commit SHA and check it out on GitHub to verify that it is a merge conflict. e.g., https://github.com/elastic/elasticsearch/commit/09056ed3229ccf42ec006eae65b5941c75452ec4

If we want a bit more insights like "Which files are typically involved in the conflicts", then uncomment out the bottom part of the script and re-run. You should see this as the output:

This repo had 127 merge conflicts; The top 5 files with the most merge conflicts are:
core/src/main/java/org/elasticsearch/common/io/stream/StreamInput.java appears in 6 conflicts
core/src/test/java/org/elasticsearch/index/query/SimpleIndexQueryParserTests.java appears in 6 conflicts
core/src/main/java/org/elasticsearch/common/io/stream/StreamOutput.java appears in 4 conflicts
core/src/main/java/org/elasticsearch/index/query/QueryParseContext.java appears in 4 conflicts
core/src/main/java/org/elasticsearch/index/query/HasChildQueryParser.java appears in 4 conflicts

Using PyDriller to Mine git Repos

• Use case: finding the most frequently modified funciton in the repo's commits
• Check https://github.com/snadi/MSRDemos/blob/master/scripts/get_most_freq_chgd_method.py
• To run:

/msrdemo# python scripts/get_most_freq_chgd_method.py --path=repos/pydriller/

It will display tuples containing the methods (including the file path) and their frequency in commits (shows 10 most modified functions)

Mining GitHub

Using Python Github APIs

• Use case: Assume you want to know the files typically involved in bug fixes. In this case, you can use Issues on the GitHub repository as your starting point for bugs and then find the files that were changed to address the bug
• Check https://github.com/snadi/MSRDemos/blob/master/scripts/get_most_errorprone_files.py for details.
• Run the script as:

python scripts/get_most_errorprone_files.py --token=token.txt --repo=ishepard/pydriller

• Note that I'm using the pydriller repo here as the target repo to analyze. You can analyze whatever repo you want
• You need to create your own token and save it in a token file that you pass to the script. This is used to authenticate with the GitHub API
• Food for thought: What are the drawbacks of the way we find files related to bug fixes in that script? Does it let us miss files? Does it let us add incorrect files? It is important to understand the implications of any assumptions/proxies we make.

Using the github APIs also allows you to access other data like releases and, for example, calculate average release time of a project.

Mining Stack Overflow Data

Using StackExchange APIs in Python

• The script https://github.com/snadi/MSRDemos/blob/master/scripts/get_so_answer_stats.py shows how you can use the StackExchange API to get the number of answer for a list of questions.

• To run:

/msrdemo# cd scripts/
/msrdemo# python get_so_answer_stats.py  

As another example for using Stack Exchange APIs, check out the code we used in our SANER '20 paper on navigating Stack Overflow answers https://github.com/ualberta-smr/StackOverflowNavCues.