Learning software testing is a neglected subject in computer science courses. Over the years, methods and tools have appeared to provide educational support for this learning. Mutation testing is a technique used to evaluate the effectiveness of test suites. Recently, a variant called extreme mutation testing that reduces computational and time costs has emerged. Descartes, an extreme mutation engine was developed. With the support of a plugin extension called Reneri, Descartes can generate a report providing information to the developer on potential reasons why mutants remain undetected. In this thesis, an extension of Visual Studio Code has been developed in order to incorporate the information generated by Descartes and Reneri. The purpose of the experiment is to assess whether the inclusion of this data can help master’s students improve their test assertions. The results showed that this information integrated into an editor was well received by the students and that it guided them towards a refinement of their suite of tests.

Although software testing is critical in software engineering, studies have shown a significant gap between students’ knowledge of software testing and the industry’s needs, hinting at the need to explore novel approaches to teach software testing. Among them, classical mutation testing has already proven to be effective in helping students. We hypothesise that extreme mutation testing could be more effective by introducing more obvious mutants to kill. In order to study this question, we organised an experiment with two undergraduate classes comparing the usage of two tools, one applying classical mutation testing, and the other one applying extreme mutation testing. The results contradicted our hypothesis. Indeed, students with access to the classic mutation testing tool obtained a better mutation score, while the others seem to have mostly covered more code. Finally, we have published and anonymised the students’ test suites in adherence to best open-science practices, and we have developed guidance based on previous evaluations and our own results.