2022-07-072022-07-072018Sánchez Jerez, A.B., Delgado Pérez, P., Medina Bulo, I. y Segura Rueda, S. (2018). Search-based mutation testing to improve performance tests. En GECCO 2018: the Genetic and Evolutionary Computation Conference (316-317), Kyoto, Japan: Association for Computing Machinery (ACM).978-1-4503-5764-7https://hdl.handle.net/11441/135086Performance bugs are common and can cause a significant deterio ration in the behaviour of a program, leading to costly issues. To detect them and reduce their impact, performance tests are typi cally applied. However, there is a lack of mechanisms to evaluate the quality of performance tests, causing many of these bugs re main unrevealed. Mutation testing, a fault-based technique to assess and improve test suites, has been successfully studied with func tional tests. In this paper, we propose the use of mutation testing together with a search-based strategy (evolutionary algorithm) to find mutants that simulate performance issues. This novel approach contributes to enhance the confidence on performance tests while reducing the cost of mutation testing.application/pdf2engAttribution-NonCommercial-NoDerivatives 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc-nd/4.0/Search-based software engineeringEvolutionary algorithmsMutation testingPerformance testingPerformance bugsinfo:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/openAccess10.1145/3205651.3205670