WIP2022-GitHub_Readme-code

Dependencies

When determining common traits that exist within README files, our program uses the spacy library to determine similarities between headers. This must be downloaded via:

pip install spacy
pip install git+https://github.com/MartinoMensio/spacy-universal-sentence-encoder.git

Optionally, a parameter is also provided USE_LARGE_MODEL under traitFinder.py. As well as USE_UNIV_SENTENCE_ENCODER, which when set to 0 will not use a sentence encoder, and instead use Spacy's large or small core datasets. USE_LARGE_MODEL may be set to 0 if you wish to use the small model, which will improve performance although provide less accurate results.

In our paper, we USE_UNIV_SENTENCE_ENCODER, given in the first download link. The small model must be downloaded via:

pip install spacy
python -m spacy download en_core_web_lg

pip install spacy
python -m spacy download en_core_web_sm

If you still receive a problem with finding the packages after installing, try:

python -m spacy download en

and restart your IDE.

Data:

The data for RQ1 and RQ2 are packaged in data/all_in_one_data.csv

RQs

RQ1

run python Wilcoxon&Cliffs_delta.py

RQ2

run python Feature_importance.py

RQ3

The labeled data located in /date/popular vs non_popular_commits 100 samples published.xlsx

Collect data from GitHub

Config.properties Format

You will need a Config.properties file in the root of the project to extract data from GitHub API in the following format

token= your_token_goes_here
user= your_GitHub_username_goes_here

For more token information, please refer to: https://docs.github.com/en/authentication/keeping-your-account-and-data-secure/creating-a-personal-access-token

Tips on running the code

• Most data collection/retrieval files can be found under data_retrieval
• Most pandas.read_csv() file name is hardcoded, feel free to change __file_name and __save_name in main as needed.
• Save a copy of your current data when you are adding new columns to the data in case of failure
• For most files does not need arguments, so you can simply click run.