Coverage is not strongly correlated with test suite effectiveness
By Laura Inozemtseva, Reid Holmes. International Conference on Software Engineering, 2014
499 citations recorded by the source corpus.
Subfields: Computer Networks and Communications, Information Systems, Software
View Paper: https://www.semanticscholar.org/paper/abd840dbcfd986e6de9102ab809c2c46e5ce47aa
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Networks and Communications
- Michael W. Hicks
- Yue Jia
- Gordon Fraser
- Mark Harman
- Reid Holmes
- Marinos Kintis
- Mike Papadakis
- Jie M. Zhang
In Information Systems
- Yue Jia
- Mike Papadakis
- Yves Le Traon
- Mark Harman
- Gordon Fraser
- René Just
- Michael D. Ernst
- Darioush Jalali
In Software
- Yue Jia
- Yves Le Traon
- Mike Papadakis
- Gordon Fraser
- Mark Harman
- René Just
- Michael D. Ernst
- Darioush Jalali
Citations in the corpus
- Chapter Six - Mutation Testing Advances: An Analysis and Survey (2019, background): “Recent studies have also identified that test suite size (number of test cases) introduces another confounding factor that should be brought under experimental control [61].”
- Evaluating Fuzz Testing (2018, background): “But the correlation may be weak [28], so directly measuring the number of bugs found is”
- Are mutants a valid substitute for real faults in software testing? (2014, background): “Differences in coverage often dominate other aspects of test suite effectiveness, and a test suite that achieves higher coverage usually detects more mutants and faults for that reason alone [16].”