To improve model performance, the model based on grouped unit tests is implemented. Originally, the model is trained to predict on the level of around 700 unit tests, which is too much. To reduce the number of predictions, unit tests are grouped into 80 groups based on their folder parents and functions in mapping.py. The performance has improved to:
|Fail (Predicted)||Pass (Predicted)|
testselect is now able to recognize 95% (94% previously) of all failures, while reducing computation by 85% (84% previously).