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Title TestEvoViz: Visual Introspection for Genetically-Based Test Coverage Evolution
Authors Andreina Cota Vidaure, Evelyn Cusi Lopez, Juan Pablo Sandoval Alcocer, Alexandre Bergel
Publication date 2020
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
Pages 1-11
Conference name IEEE Working Conference on Software Visualization
Publisher IEEE Computer Society Press (Los Alamitos, CA, USA)
Reference URL View reference page