MOTSD: a multi-objective test selection tool using test suite diagnosability
Daniel Correia, Rui Abreu, Pedro de Alcântara dos Santos Neto, João Nadkarni · 2019
Performing regression testing on large software systems becomes unfeasible as it takes too long to run all the test cases every time a change is made. The main motivation of this work was to provide a faster and earlier feedback loop to the developers at OutSystems when a change is made. The developed tool, MOTSD, implements a multi-objective test selection approach in a C# code base using a test suite diagnosability metric and historical metrics as objectives and it is powered by a particle swarm optimization algorithm. We present implementation challenges, current experimental results and limitations of the tool when applied in an industrial context. Screencast demo link: https://www.youtube.com/watch?v=CYMfQTUu2BE