Abstract
We present Chameleon, a new approach for adaptively changing search heuristics during concolic testing. Search heuristics play a central role in concolic testing as they mitigate the path-explosion problem by focusing on particular program paths that are likely to increase code coverage as quickly as possible. A variety of techniques for search heuristics have been proposed over the past decade. However, existing approaches are limited in that they use the same search heuristics throughout the entire testing process, which is inherently insufficient to exercise various execution paths. Chameleon overcomes this limitation by adapting search heuristics on the fly via an algorithm that learns new search heuristics based on the knowledge accumulated during concolic testing. Experimental results show that the transition from the traditional non-adaptive approaches to ours greatly improves the practicality of concolic testing in terms of both code coverage and bug-finding.
| Original language | English |
|---|---|
| Title of host publication | ESEC/FSE 2019 - Proceedings of the 2019 27th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering |
| Editors | Sven Apel, Marlon Dumas, Alessandra Russo, Dietmar Pfahl |
| Publisher | Association for Computing Machinery, Inc |
| Pages | 235-245 |
| Number of pages | 11 |
| ISBN (Electronic) | 9781450355728 |
| DOIs | |
| Publication status | Published - 2019 Aug 12 |
| Event | 27th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, ESEC/FSE 2019 - Tallinn, Estonia Duration: 2019 Aug 26 → 2019 Aug 30 |
Publication series
| Name | ESEC/FSE 2019 - Proceedings of the 2019 27th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering |
|---|
Conference
| Conference | 27th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, ESEC/FSE 2019 |
|---|---|
| Country | Estonia |
| City | Tallinn |
| Period | 19/8/26 → 19/8/30 |
Fingerprint
Keywords
- Concolic Testing
- Dynamic Symbolic Execution
- Online Learning
ASJC Scopus subject areas
- Artificial Intelligence
- Software
Cite this
Concolic testing with adaptively changing search heuristics. / Cha, Sooyoung; Oh, Hakjoo.
ESEC/FSE 2019 - Proceedings of the 2019 27th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering. ed. / Sven Apel; Marlon Dumas; Alessandra Russo; Dietmar Pfahl. Association for Computing Machinery, Inc, 2019. p. 235-245 (ESEC/FSE 2019 - Proceedings of the 2019 27th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Concolic testing with adaptively changing search heuristics
AU - Cha, Sooyoung
AU - Oh, Hakjoo
PY - 2019/8/12
Y1 - 2019/8/12
N2 - We present Chameleon, a new approach for adaptively changing search heuristics during concolic testing. Search heuristics play a central role in concolic testing as they mitigate the path-explosion problem by focusing on particular program paths that are likely to increase code coverage as quickly as possible. A variety of techniques for search heuristics have been proposed over the past decade. However, existing approaches are limited in that they use the same search heuristics throughout the entire testing process, which is inherently insufficient to exercise various execution paths. Chameleon overcomes this limitation by adapting search heuristics on the fly via an algorithm that learns new search heuristics based on the knowledge accumulated during concolic testing. Experimental results show that the transition from the traditional non-adaptive approaches to ours greatly improves the practicality of concolic testing in terms of both code coverage and bug-finding.
AB - We present Chameleon, a new approach for adaptively changing search heuristics during concolic testing. Search heuristics play a central role in concolic testing as they mitigate the path-explosion problem by focusing on particular program paths that are likely to increase code coverage as quickly as possible. A variety of techniques for search heuristics have been proposed over the past decade. However, existing approaches are limited in that they use the same search heuristics throughout the entire testing process, which is inherently insufficient to exercise various execution paths. Chameleon overcomes this limitation by adapting search heuristics on the fly via an algorithm that learns new search heuristics based on the knowledge accumulated during concolic testing. Experimental results show that the transition from the traditional non-adaptive approaches to ours greatly improves the practicality of concolic testing in terms of both code coverage and bug-finding.
KW - Concolic Testing
KW - Dynamic Symbolic Execution
KW - Online Learning
UR - http://www.scopus.com/inward/record.url?scp=85071908637&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85071908637&partnerID=8YFLogxK
U2 - 10.1145/3338906.3338964
DO - 10.1145/3338906.3338964
M3 - Conference contribution
T3 - ESEC/FSE 2019 - Proceedings of the 2019 27th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering
SP - 235
EP - 245
BT - ESEC/FSE 2019 - Proceedings of the 2019 27th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering
A2 - Apel, Sven
A2 - Dumas, Marlon
A2 - Russo, Alessandra
A2 - Pfahl, Dietmar
PB - Association for Computing Machinery, Inc
ER -