Name: Flask
URL: https://github.com/pallets/flask
Number of lines of code and the tool used to count it: 782430 counted using Lizard
Programming language: Python
The existing tool used for measuring coverage is coverage.py. It was executed using the following command:
coverage run -m pytest
Group member name: Jannes van den Bogert
Function 1 name: 'get_send_file_max_age'
Commit made: get_send_file_max_age
Function 2 name: dispatch_request
Commit made: Commit for dispatch_request
Group member name: Wasim Albarazi
Function 1: 'show_server_banner'
Commit made: Commit for show_server_banner
Function 2: 'make_config'
Commit made: Commit for make_config
Group member name: Alexandr Costei
Function 1: 'create_url_adapter'
Commit made: https://github.com/wasimic311/flask/commit/510783b87887defc464210f6a2b30c539acc1ce8
Function 2: 'AppContext.Pop'
Commit made: https://github.com/wasimic311/flask/commit/b048625880ba532b8e503c6c8d65ccc9e761f576
Test 1: 'create_url_adapter'
Commit made: https://github.com/wasimic311/flask/commit/510783b87887defc464210f6a2b30c539acc1ce8
The coverage was improved by 64%, because the tests now cover all the branches in the create_url_adapter function, including scenarios for requests with and without subdomains and handling various configurations.
Test 2: 'AppContext.Pop'
Commit made: https://github.com/wasimic311/flask/commit/b048625880ba532b8e503c6c8d65ccc9e761f576
The coverage was improved by 25%, because the tests now cover all branches in the AppContext.pop method, including scenarios for handling exceptions and context mismatches.
Group member name: Jannes van den Bogert
Test 1 name: test_get_send_file_max_age
Commit made: Commit for test_make_config.py
The coverage improved by 54%, from 46% to 100%.
Test 2 name: test_dispatch_request
Commit made: Commit for test_make_config.py
The coverage improved by 58%, from 42% to 100%.
Group member name: Wasim Albarazi
Test 1: test_show_server_banner.py
Commit made: Commit for test_show_server_banner
Old:
New:
The coverage improved by 25%, from 69% to 94%.
This improvement is due to:
New Test Cases: Added tests for show_server_banner under different conditions, such as with and without reloader and with no import path. Branch Coverage: Explicit checks ensure that all branches in the show_server_banner function are covered. Coverage Reporting: Added functionality to save coverage data to a JSON file, ensuring comprehensive coverage tracking.
These additions ensure that almost all code paths are executed during testing.
Group member name: Wasim Albarazi
Test 1: test_make_config.py
Commit made: Commit for test_make_config.py
Old:
New:
The coverage improved by 27%, from 73% to 100%.
This improvement is due to:
New Test Cases: Added tests for make_config under default and instance-relative conditions. Branch Coverage: Explicit checks for all branches in make_config.
These additions ensure all code paths are tested.
Alexandr Costei: During the selection of the functions that had to be tested, I picked 2 functions that did not have 100% branch coverage: "create_url_adapter" and "AppContext.Pop". In order to create the necessary tests, I have: - Analyzed the existing code to identify the branches and edge cases that needed to be tested. - Wrote new unit tests to cover these scenarios. - Integrated branch tracking to monitor and ensure coverage improvements.
Jannes van den Bogert: I was responsible for designing and implementing two tests for the Flask application. The tests targeted two specific functions: get_send_file_max_age and dispatch_request. My contributions were helping in enhancing the test coverage from partial to complete for these functions, achieving a significant increase in overall coverage.
Wasim Albarazi: In our project, I was responsible for designing and implementing tests for two critical functions in our Flask application: show_server_banner and make_config. The tests were organized into two separate files, test_make_config.py and test_show_server_banner.py, each focused on validating the functionality and reliability of their respective functions. Additionally, I developed a custom coverage tracking tool named coverage_tracker.py. This tool was instrumental in monitoring the test coverage across our application. It tracks the coverage of the test executions and stores the results in a JSON file called coverage_result.json. This implementation provided us with detailed insights into our test coverage, helping to ensure that we achieved comprehensive testing and improved the overall quality and robustness of our application.