Name
Abstract | ||
|---|---|---|
Fixing bugs is a lengthy process which currently requires several manual steps to be undertaken by a developer. Reproducing a crash often takes a significant amount of time during this process, as it requires a developer to identify where the crash occurred and where the taint began, thus leading to the crash. Several tools, such as EvoCrash, STAR, and Beacon, have been created to automate this process. Proposed research includes creating a benchmark dataset, performing an empirical evaluation of fitness functions for crash reproduction, and combining both evolutionary and static approaches to reduce search spaces and increase the effectiveness of automated crash reproduction tools. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1145/3510454.3517064 | 2022 IEEE/ACM 44th International Conference on Software Engineering: Companion Proceedings (ICSE-Companion) |
Keywords | DocType | ISSN |
automation,crash reproduction,evolutionary computing,software testing,symbolic execution | Conference | 2574-1926 |
ISBN | Citations | PageRank |
978-1-6654-9599-8 | 0 | 0.34 |
References | Authors | |
10 | 1 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Philip Oliver | 1 | 0 | 0.34 |