Name
Abstract | ||
|---|---|---|
Mutation analysis is an established technique for measuring the completeness and quality of a test suite. Despite four decades of research on this technique, its use in large systems is still rare, in part due to computational requirements and high numbers of false positives. We present our experiences using mutation analysis on the Linux kernel's RCU (Read Copy Update) module, where we adapt existing techniques to constrain the complexity and computation requirements. We show that mutation analysis can be a useful tool, uncovering gaps in even well-tested modules like RCU. This experiment has so far led to the identification of 3 gaps in the RCU test harness, and 2 bugs in the RCU module masked by those gaps. We argue that mutation testing can and should be more extensively used in practice. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/ICSTW.2017.26 | 2017 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW) |
Keywords | Field | DocType |
Mutation Analysis,Linux kernel | Test suite,Kernel (linear algebra),Test harness,Computer science,Software bug,Read-copy-update,Artificial intelligence,Completeness (statistics),Machine learning,Embedded system,Linux kernel,False positive paradox | Conference |
ISSN | ISBN | Citations |
2159-4848 | 978-1-5090-6677-3 | 4 |
PageRank | References | Authors |
0.38 | 36 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Iftekhar Ahmed | 1 | 89 | 6.43 |
| Carlos Jensen | 2 | 333 | 26.67 |
| Alex Groce | 3 | 1289 | 73.53 |
| Paul E. McKenney | 4 | 279 | 30.11 |