Abstract

Genetic algorithms are an efficient mechanism to generate unit tests. Automatically generated unit tests are known to be an important asset to identify software defects and define oracles. However, configuring the test generation is a tedious activity for a practitioner due to the inherent difficulty to adequately tuning the generation process. This paper presents TestEvoViz, a visual technique to introspect the generation of unit tests using genetic algorithms. TestEvoViz offers the practitioners a visual support to expose some of the decisions made by the test generation. A number of case studies are presented to illustrate the expressiveness of TestEvoViz to understand the effect of the algorithm configuration.Artifact - https://github.com/andreina-covi/ArtifactSSG.