Print Email Facebook Twitter Effective and Efficient API Misuse Detection via Exception Propagation and Search-Based Testing Title Effective and Efficient API Misuse Detection via Exception Propagation and Search-Based Testing Author Kechagia, M. (University College London (UCL)) Devroey, Xavier (TU Delft Software Engineering) Panichella, A. (TU Delft Software Engineering) Gousios, G. (TU Delft Software Engineering) van Deursen, A. (TU Delft Software Technology) Contributor Moller, Anders (editor) Zhang, Dongmei (editor) Department Software Technology Date 2019 Abstract Application Programming Interfaces (APIs) typically come with (implicit) usage constraints. The violations of these constraints (API misuses) can lead to software crashes. Even though there are several tools that can detect API misuses, most of them suffer from a very high rate of false positives. We introduce Catcher, a novel API misuse detection approach that combines static exception propagation analysis with automatic search-based test case generation to effectively and efficiently pinpoint crash-prone API misuses in client applications. We validate Catcher against 21 Java applications, targeting misuses of the Java platform’s API. Our results indicate that Catcher is able to generate test cases that uncover 243 (unique) API misuses that result in crashes. Our empirical evaluation shows that Catcher can detect a large number of misuses (77 cases) that would remain undetected by the traditional coverage-based test case generator EvoSuite. Additionally, on average, Catcher is eight times faster than EvoSuite in generating test cases for the identified misuses. Finally, we find that the majority of the exceptions triggered by Catcher are unexpected to developers, i.e., not only unhandled in the source code but also not listed in the documentation of the client applications. Subject API misuseSearch-based software testingSoftware crashStatic exception propagation To reference this document use: http://resolver.tudelft.nl/uuid:b3cc4b4c-a460-4e2d-9dd1-7b1f45368525 DOI https://doi.org/10.1145/3293882.3330552 Publisher Association for Computing Machinery (ACM), New York ISBN 978-1-4503-6224-5 Source ISSTA 2019: Proceedings of the 28th ACM SIGSOFT International Symposium on Software Testing and Analysis Event ISSTA 2019: 28th ACM SIGSOFT International Symposium on Software Testing and Analysis, 2019-07-15 → 2019-07-19, Beijing, China Part of collection Institutional Repository Document type conference paper Rights © 2019 M. Kechagia, Xavier Devroey, A. Panichella, G. Gousios, A. van Deursen Files PDF catcher.pdf 1.03 MB Close viewer /islandora/object/uuid:b3cc4b4c-a460-4e2d-9dd1-7b1f45368525/datastream/OBJ/view