Education

How do you get 4th graders (16yo.) to understand software engineering in 1h30? That’s the challenge we (Jérôme Maquoi, Benoît Vanderose and Xavier Devroey) set ourselves on Thursday April 25, 2024. Rather than making them write code, we chose another route: get them to build a 16-floors tower of wooden blocks in under 32 minutes with constraints similar to a software development team in full rush. 😁

The widespread digitalization of society and the increasing complexity of software make it essential to develop high-quality software testing suites. In recent years, several techniques for learning software testing have been developed, including techniques based on mutation testing. At the same time, the recent performance of language models in both text comprehension and generation, as well as code generation, makes them potential candidates for assisting students in learning how to develop tests. To confirm this, an experiment was carried out with students with little experience in software testing, comparing the results obtained by some students using a report from a classic mutation testing tool and a report augmented with hints generated by a language model. The results seem promising since the augmented reports improved the mutation score and mutant coverage within the group more generally than the other reports. In addition, the augmented reports seem to have been most effective in testing methods for modifying and retrieving private variable values.

On July 4, the faculty’s teaching staff participated in a half-day training session on gender questions and representations in Computer Science courses. This training is part of the results of the research project Gender Equals Future: 011 for IT, in which Interface3.Namur, Form@Nam and the University of Namur are partners. It was an opportunity to take a closer look at the situation, based on figures taken from the annual report on gender equality at the University of Namur (2020-2021), and to break down a few clichés about women’s involvement in computer science studies and the academic world. Participants were also introduced to the difference between the concepts of sex and gender, common cognitive biases, and stereotypes. The training ended with a brainstorming session on some practical actions to be implemented at the faculty.

L’application de tests automatiques au code soumis par les étudiants sur une plateforme de correction automatique est un outil utile pour le corps enseignant. Il permet de fournir de meilleurs retours, sur plus d’exercices, créés plus rapidement. Des méthodes des tests automatiques sont analysées et une sélection est faite sur ceux qui, de par leurs caractéristiques, sont les plus intéressants dans le contexte de la correction automatique des codes d’étudiants. Les méthodes retenues sont le fuzzing en boite grise et le test de combinaisons d’appels sur une structure donnée. L’efficacité de celles-ci est discutée et une application pratique est développée sous la forme d’une librairie de test qui s’intègre dans la plateforme de correction automatique Inginious. Les limitations sont analysées et un protocole de test des modifications apportées par celles-ci est ensuite proposé pour pouvoir quantifier les gains apportés via une expérience pratique.

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.