CPC G06F 8/77 (2013.01) | 18 Claims |
1. A computer-implemented method comprising:
generating, by one or more processors of a computing system, training data comprising:
a first set of pairs wherein each pair of the first set of pairs comprises a commit message and a corresponding code change in an existing project; and
a second set of pairs wherein each pair of the second set of pairs comprises a commit message and a randomly selected code change that is different than the corresponding code change for the commit message;
training, by the one or more processors of the computing system, a machine learning model using the generated training data to generate a trained machine learning model configured to generate a score indicating a level of discrepancy between a commit message and a corresponding code change;
receiving, by the one or more processors of the computing system, a commit comprising a given commit message and a given corresponding code change;
analyzing, using the trained machine learning model, the given commit message and given corresponding code change to generate a score indicating the level of discrepancy between the given commit message and the given corresponding code change of the received commit;
determining that the generated score is greater than a threshold value; and
providing a notification to request an update to the given commit message before the commit will be accepted in a project repository.
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