Title
TestEvoViz: Visual Introspection for Genetically-Based Test Coverage Evolution
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.
Year
DOI
Venue
2020
10.1109/VISSOFT51673.2020.00005
2020 Working Conference on Software Visualization (VISSOFT)
Keywords
DocType
ISBN
visualization,genetic algorithms,test generation
Conference
978-1-7281-9915-3
Citations 
PageRank 
References 
0
0.34
15
Authors
4