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FSE 2019

MOTSD: a multi-objective test selection tool using test suite diagnosability

Daniel Correia, Rui Abreu, Pedro Santos, João Nadkarni

PDFDOI 10.1145/3338906.3341187dblp

Abstract

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

BibTeX
@inproceedings{Correia-al:FSE19,
  author    = {Daniel Correia and
               Rui Abreu and
               Pedro Santos and
               Jo{\~{a}}o Nadkarni},
  title     = {{MOTSD:} a multi-objective test selection tool using test suite diagnosability},
  booktitle = {{ESEC/SIGSOFT} {FSE}},
  pages     = {1070--1074},
  publisher = {{ACM}},
  year      = {2019},
}

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