Resource-based Test Case Generation for RESTful Web Services

Nowadays, RESTful web services are widely used for building enterprise applications. In this paper, we propose an enhanced search-based method for automated system test generation for RESTful web services. This method exploits domain knowledge on the handling of HTTP resources, and it is integrated in the Many Independent Objectives (MIO) search algorithm. MIO is an evolutionary algorithm specialized for system test case generation with the aim of maximizing code coverage and fault finding. Our approach builds on top of the MIO by implementing a set of effective templates to structure test actions, based on the semantics of HTTP methods, used to manipulate the web services' resources. We propose four novel sampling strategies for the test cases that can use one or more of these test actions. The strategies are further supported with a set of new, specialized mutation operators that take into account the use of these resources in the generated test cases. We implemented our approach as an extension to the EvoMaster tool, and evaluated it on seven open-source RESTful web services. The results of our empirical study show that our novel, resource-based sampling strategies obtain a significant improvement in performance over the baseline MIO (up to +42% coverage).