通过异常传播和基于搜索的测试进行有效和高效的API误用检测

M. Kechagia, Xavier Devroey, Annibale Panichella, Georgios Gousios, A. Deursen
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引用次数: 7

摘要

应用程序编程接口(api)通常带有(隐式)使用约束。违反这些约束(API误用)可能导致软件崩溃。尽管有几种工具可以检测API的滥用,但大多数工具的误报率非常高。我们介绍了一种新的API误用检测方法Catcher,它将静态异常传播分析与基于自动搜索的测试用例生成相结合,从而有效地查明客户端应用程序中容易导致崩溃的API误用。我们针对21个Java应用程序验证了Catcher,针对Java平台API的误用。我们的结果表明,Catcher能够生成测试用例,发现243个(独特的)导致崩溃的API误用。我们的经验评估表明,Catcher可以检测到传统的基于覆盖率的测试用例生成器EvoSuite无法检测到的大量滥用(77例)。此外,在为已识别的错误生成测试用例方面,Catcher的平均速度是EvoSuite的8倍。最后,我们发现Catcher触发的大多数异常对开发人员来说都是意料之外的,也就是说,不仅在源代码中没有处理,而且在客户端应用程序的文档中也没有列出。
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Effective and efficient API misuse detection via exception propagation and search-based testing
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.
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ISSTA '22: 31st ACM SIGSOFT International Symposium on Software Testing and Analysis, Virtual Event, South Korea, July 18 - 22, 2022 ISSTA '21: 30th ACM SIGSOFT International Symposium on Software Testing and Analysis, Virtual Event, Denmark, July 11-17, 2021 Automatic support for the identification of infeasible testing requirements Program-aware fuzzing for MQTT applications ISSTA '20: 29th ACM SIGSOFT International Symposium on Software Testing and Analysis, Virtual Event, USA, July 18-22, 2020
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