Many-Objective Test Suite Generation for Software Product Lines





Publicado en

Actas de las XXV Jornadas de Ingeniería del Software y Bases de Datos (JISBD 2021)

Licencia Creative Commons


A Software Product Line (SPL) is a set of products built from a number of features, the set of valid products being dened by a feature model. Typically, it does not make sense to test all products dened by an SPL and one instead chooses a set of products to test (test selection) and, ideally, derives a good order in which to test them (test prioritisation). Since one cannot know in advance which products will reveal faults, test selection and prioritisation are normally based on objective functions that are known to relate to likely effectiveness or cost. This article introduces a new technique, the grid-based evolution strategy (GrES), which considers several objective functions that assess a selection or prioritisation and aims to optimise on all of these. The problem is thus a many-objective optimisation problem. We use a new approach, in which all of the objective functions are considered but one (pairwise coverage) is seen as the most important. We also derive a novel evolution strategy based on domain knowledge. The results of the evalua- tion, on randomly generated and realistic feature models, were promising, with GrES outperforming previously proposed techniques and a range of many-objective optimisation algorithms.


Acerca de Hierons, Rob

Palabras clave

Evolutionary Algorithms, Many-objectives Optimization, Search-Based Software Engineering, Software Product Lines, Testing
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