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...
Uloženo v:
| Vydáno v: | 2022 IEEE/ACM 44th International Conference on Software Engineering: Companion Proceedings (ICSE-Companion) s. 331 - 333 |
|---|---|
| Hlavní autor: | |
| Médium: | Konferenční příspěvek |
| Jazyk: | angličtina |
| Vydáno: |
IEEE
01.05.2022
|
| Témata: | |
| On-line přístup: | Získat plný text |
| Tagy: |
Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
|
| 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 |