Deep Multiple Assertions Generation
Hailong Wang, Tongtong Xu, Bei Wang · 2024
Software testing is one of the most crucial parts of the software development life cycle. Developers spend substantial amount of time and efforts on software testing. Recently, there has been a growing scholarly interest in the automation of software testing. However, recent studies have revealed significant limitations in the quality and efficacy of the generated assert statements. These limitations primarily arise due to: (i) the inherent complexity involved in generating assert statements that are both meaningful and effective; (ii) the challenge of capturing the relationship between multiple assertions in a single test case. In recent research, deep learning techniques have been employed to generate meaningful assertions. However, it is typical for a single assertion to be generated for each test case, which contradicts the current situation where over 40% of test cases contain multiple assertions.