GitHub is the world’s largest version control and source code management service with more than 50 million developers worldwide. More than 100 million repositories are publicly available which can be mined using their APIs. Data-driven analysis on usch repositories help to allocate resources towards project maintenance, improve productivity, project’s cost-effectiveness, and reduce the likelihood of bugs. In issue tracking systems developers can report tickets or potential problems, manage them and keep track of their progress. Similar to the other platform GitHub provides a issue tracker along with the labeling support. Accurate Classification of these issue-reports can help monitor the software evolution process and enable better tracking for various industrial stakeholders. This work prosposes a classification method of issue-reports into “bug-report”, “feature-request”, and “enhancement” categories.

The following list explains as in which order the artifacts should be executed:

1. bigquery_query.txt 1.1. Goto Google big query tool 1.2. Set the SQL dialect as legacy 1.3. Run the query provided in the "bigQuery.txt" text file on Google big query platform 1.4. Save the result as language_repo.csv

2. language_repo_fetch.ipynb

3. repo_issue_fetch.ipynb

4. Issue Classification.ipynb (Use GPU backend on Google Collab, this is the issue classification model)