Test scenario generation for feature-based context-oriented software systems

Feature-based context-oriented programming reconciles ideas from context-oriented programming, feature modelling and dynamic software product lines. It offers a programming language, architecture, tools and methodology to develop software systems consisting of contexts and features that can become a...

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Vydáno v:The Journal of systems and software Ročník 197; s. 111570
Hlavní autoři: Martou, Pierre, Mens, Kim, Duhoux, Benoît, Legay, Axel
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier Inc 01.03.2023
Témata:
Combinatorial interaction testing
Context-oriented programming
Dynamic software product lines
Feature modelling
Satisfiability checking (SAT)
Software testing
Software testing
Satisfiability checking (SAT)
Software and its engineering: Software testing and debugging
Dynamic software product lines
Context specific languages
Context-oriented programming
Combinatorial interaction testing
Software product lines
Feature modelling
ISSN:0164-1212, 1873-1228
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Shrnutí:Feature-based context-oriented programming reconciles ideas from context-oriented programming, feature modelling and dynamic software product lines. It offers a programming language, architecture, tools and methodology to develop software systems consisting of contexts and features that can become active at run-time to offer the most appropriate behaviour depending on the actual context of use. Due to their high run-time adaptivity, dedicated tool support to test such systems is needed. Building upon a pairwise combinatorial interaction testing approach from the domain of software product lines, we implement an algorithm to generate automatically a small set of relevant test scenarios, ordered to minimise the number of context activations between tests. We also explore how the generated scenarios can be enhanced incrementally when the software evolves, and how useful the proposed testing approach is in practice. •Generation of a test suite for context-oriented systems with logarithmic growth.•Prioritisation of the tests with context-oriented criteria (creation cost).•Social experiment shows the usefulness of our approach for design testing.•Test suite augmentation algorithm for new system version (cost reduced by 34).
ISSN:0164-1212
1873-1228
DOI:10.1016/j.jss.2022.111570