μ2: Using Mutation Analysis to Guide Mutation-Based Fuzzing
Coverage-guided fuzzing is a popular tool for finding bugs. This paper introduces μ 2 , a strategy for extending coverage-guided fuzzing with mutation analysis, which previous work has found to be better correlated with test effectiveness than code coverage. μ 2 was implemented in Java using the JQF...
Uložené v:
| Vydané v: | 2022 IEEE/ACM 44th International Conference on Software Engineering: Companion Proceedings (ICSE-Companion) s. 331 - 333 |
|---|---|
| Hlavný autor: | |
| Médium: | Konferenčný príspevok.. |
| Jazyk: | English |
| Vydavateľské údaje: |
IEEE
01.05.2022
|
| Predmet: | |
| On-line prístup: | Získať plný text |
| Tagy: |
Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
|
| Shrnutí: | Coverage-guided fuzzing is a popular tool for finding bugs. This paper introduces μ 2 , a strategy for extending coverage-guided fuzzing with mutation analysis, which previous work has found to be better correlated with test effectiveness than code coverage. μ 2 was implemented in Java using the JQF framework and the default mutations used by PIT. Initial evaluation shows increased performance when using μ 2 as compared to coverage-guided fuzzing. |
|---|---|
| DOI: | 10.1145/3510454.3522682 |