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This repository contains functions to store knowledge for the bot, to use the knowledge stored by the bot to evaluate some statistics.


pipenv install --dev

Usage - Create Bot Knowledge

  1. You can extract knowledge from a project using the following command:
GITHUB_ACCESS_TOKEN=<github_acess_token> PYTHONPATH=. pipenv run srcopsmetrics/ --project <project_name> -c True

Usage - Visualize Project Statistics

PYTHONPATH=. pipenv run srcopsmetrics/ --project <project_name> -v True


For each project is possible to obtain the following plots:

MTTR-in-time-<name-project>.png –> Mean time to Review (MTTR) variation after each PR approved in time.

MTTR-in-time-<name-project>-authors.png –> Mean time to Review (MTTR) variation after each PR approved for each author in time.

thoth-station-<name-project>.png –> Time to Review (TTR) variation after each PR approved.

thoth-station-<name-project>-authors.png –> Time to Review (TTR) variation after each PR approved per reviwer.

Usage - Reviewer Reccomender

PYTHONPATH=. pipenv run srcopsmetrics/ --project <project_name> -r True

If there are bots in the list of contributors of your project you can add them to the list at the beginning of the file. In this way you can receive the percentage of the work done by humans vs bots.


number_reviewer flag is set to 2

Final Score for Reviewers assignment

The final score for the selection of the reviewers, it is based on the following contributions. (Number of reviewers is by default 2, but it can be changed)

  1. Number of PR reviewed respect to total number of PR reviewed by the team.
  2. Mean time to review a PR by reviewer respect to team repostiory MTTR.
  3. Mean length of PR respect to minimum value of PR length for a specific label.
  4. Number of commits respect to the total number of commits in the repository.

5. Time since last review compared to time from the first review of the project respect to the present time. (Time dependent contribution)

Each of the contribution as a weight factor k. If all weight factors are set to 1, all contributions to the final score have the same weight.

Example results

Repository  PullRequest n.  Commits n.  PullRequestRev n.           MTTFR     MTTR

thoth-station/performance 33 38 20 0:17:30.500000 0:46:28 INFO:reviewer_recommender:——————————————————————————-

Contrib PR n. PR % PRRev n. PRRev % MPRLen Rev n. MRL MTTFR MTTR TLR Comm n. Comm % Bot fridex 17 0.515152 13 0.65 S 21 3.0 0:02:44 0:31:10 40 days 00:08:36.857380 19 0.5 False pacospace 16 0.484848 7 0.35 M 9 1.0 1:01:46 1:01:46 40 days 05:00:39.857380 19 0.5 False

Contrib C1 C2 C3 C4 C5 Score pacospace 0.484848 0.752294 1.00000 0.5 1 0.337028 fridex 0.515152 1.490909 0.22449 0.5 1 0.159314

INFO:reviewer_recommender:Number of reviewers requested: 2 INFO:reviewer_recommender:Reviewers: [‘pacospace’ ‘fridex’]

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