Renaud Rwemalika

Renaud Rwemalika, Sarra Habchi, Mike Papadakis et al.

Test smells are known as bad development practices that reflect poor design and implementation choices in software tests. Over the last decade, test smells were heavily studied to measure their prevalence and impacts on test maintainability. However, these studies focused mainly on the unit level and to this day, the work on system tests that interact with the System Under Test through a Graphical User Interface remains limited. To fill the gap, we conduct an exploratory analysis of test smells occurring in System User Interactive Tests (SUIT). First, based on a multi-vocal literature review, we propose a catalog of 35 SUIT-specific smells. Then, we conduct an empirical analysis to assess the prevalence and refactoring of these smells in 48 industrial test suites and 12 open-source projects. We show that the same type of smells tends to appear in industrial and open-source projects, but the symptoms are not addressed in the same way. Smells such as Obscure Test, Sneaky Checking, and Over Checking show symptoms in more than 70% of the tests. Yet refactoring actions are much less frequent with less than 50% of the affected tests ever undergoing refactoring. Interestingly, while refactoring actions are rare, some smells, such as Narcissistic, disappear through the removal of old symptomatic tests and the introduction of new tests not presenting such symptoms.

Maxime Cordy, Renaud Rwemalika, Mike Papadakis et al.

Much research on software testing makes an implicit assumption that test failures are deterministic such that they always witness the presence of the same defects. However, this assumption is not always true because some test failures are due to so-called flaky tests, i.e., tests with non-deterministic outcomes. Unfortunately, flaky tests have major implications for testing and test-dependent activities such as mutation testing and automated program repair. To deal with this issue, we introduce a test flakiness assessment and experimentation platform, called FlakiMe, that supports the seeding of a (controllable) degree of flakiness into the behaviour of a given test suite. Thereby, FlakiMe equips researchers with ways to investigate the impact of test flakiness on their techniques under laboratory-controlled conditions. We use FlakiME to report results and insights from case studies that assesses the impact of flakiness on mutation testing and program repair. These results indicate that a 5% of flakiness failures is enough to affect the mutation score, but the effect size is modest (2% - 4% ), while it completely annihilates the ability of program repair to patch 50% of the subject programs. We also observe that flakiness has case-specific effects, which mainly disrupts the repair of bugs that are covered by many tests. Moreover, we find that a minimal amount of user feedback is sufficient for alleviating the effects of flakiness.