(Un-)Covering Equivalent Mutants

@article{Schuler2010UnCoveringEM,
  title={(Un-)Covering Equivalent Mutants},
  author={David Schuler and Andreas Zeller},
  journal={2010 Third International Conference on Software Testing, Verification and Validation},
  year={2010},
  pages={45-54}
}
Mutation testing measures the adequacy of a test suite by seeding artificial defects (mutations) into a program. If a test suite fails to detect a mutation, it may also fail to detect real defects-and hence should be improved. However, there also are mutations which keep the program semantics unchanged and thus cannot be detected by any test suite. Such equivalent mutants must be weeded out manually, which is a tedious task. In this paper, we examine whether changes in coverage can be used to… CONTINUE READING
Highly Influential
This paper has highly influenced 17 other papers. REVIEW HIGHLY INFLUENTIAL CITATIONS
Highly Cited
This paper has 141 citations. REVIEW CITATIONS
78 Citations
20 References
Similar Papers

Citations

Publications citing this paper.
Showing 1-10 of 78 extracted citations

142 Citations

0102030'11'13'15'17
Citations per Year
Semantic Scholar estimates that this publication has 142 citations based on the available data.

See our FAQ for additional information.

References

Publications referenced by this paper.
Showing 1-10 of 20 references

namically discovering likely program invariants to support program evolution

  • J. Pan
  • IEEE Trans . on Software Engineering
  • 2001

Similar Papers

Loading similar papers…