Machine learning (ML) may enable effective automated test generation. We characterize emerging research, examining testing practices, researcher goals, ML techniques applied, evaluation, and challenges in this intersection by performing. perform a systematic mapping study on sample of 124 publications. generates input for system, GUI, unit, performance, combinatorial or improves the performance...

Test impact analysis is an approach to obtain a subset of tests impacted by code changes. This mainly applied unit testing where the link between and its associated easy obtain. On integration level, however, it not straightforward find such programmatically, especially when are held into separate repositories. We propose for selecting based on runtime changes reduce test execution overhead. pr...