A Theoretical and Empirical Analysis of Program Spectra Diagnosability

A Theoretical and Empirical Analysis of Program Spectra Diagnosability

Perez, Alexandre (Universidade do Porto)
Abreu, Rui (University of Lisbon)
van Deursen, A. (TU Delft Software Technology)

Software Technology

2019-03-01

Current metrics for assessing the adequacy of a test-suite plainly focus on the number of components (be it lines, branches, paths) covered by the suite, but do not explicitly check how the tests actually exercise these components and whether they provide enough information so that spectrum-based fault localization techniques can perform accurate fault isolation. We propose a metric, called DDU, aimed at complementing adequacy measurements by quantifying a test-suite's diagnosability, i.e., the effectiveness of applying spectrum-based fault localization to pinpoint faults in the code in the event of test failures. Our aim is to increase the value generated by creating thorough test-suites, so they are not only regarded as error detection mechanisms but also as effective diagnostic aids that help widely-used fault-localization techniques to accurately pinpoint the location of bugs in the system. We have performed a topology-based simulation of thousands of spectra and have found that DDU can effectively establish an upper bound on the effort to diagnose faults. Furthermore, our empirical experiments using the Defects4J dataset show that optimizing a test suite with respect to DDU yields a 34 percent gain in spectrum-based fault localization report accuracy when compared to the standard branch-coverage metric.

Testing
coverage
diagnosability

http://resolver.tudelft.nl/uuid:10485869-51dc-4e28-be80-0a40dd5a37f1

https://doi.org/10.1109/TSE.2019.2895640

1939-3520

IEEE Transactions on Software Engineering, 47 (2), 412-431

Institutional Repository

journal article

© 2019 Alexandre Perez, Rui Abreu, A. van Deursen