Abstract
Needs for mass customization and economies of scale have pushed engineers to develop Software Product Lines (SPLs). SPLs are families of products sharing commonalities and exhibiting differences, built by reusing software assets abstractly represented by features. Feature models describe the constraints that link the features and allow the configuration of tailored software products. Common SPLs involve hundreds, even thousands of features, leading to billions of possible software products. As a result, testing a product line is challenging due to the enormous size of the possible products. Existing techniques focus on testing based on the product line's feature model by selecting a limited set of products to test. Being created manually or reverse-engineered, feature models are prone to errors impacting the generated test suites. In this paper, we examine ability of test suites to detect such errors. In particular, we propose two mutation operators to derive erroneous feature models (mutants) from an original feature model and assess the capability of the generated original test suite to kill the mutants. Experimentation on real feature models demonstrate that dissimilar tests suites have a higher mutant detection ability than similar ones, thus validating the relevance of similarity-driven product line testing.
Original language | English |
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Title of host publication | Proceedings - IEEE 6th International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2013 |
Publisher | IEEE |
Pages | 188-197 |
Number of pages | 10 |
DOIs | |
Publication status | Published - 9 Sept 2013 |
Event | IEEE 6th International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2013 - Luxembourg, Luxembourg Duration: 18 Mar 2013 → 20 Mar 2013 |
Conference
Conference | IEEE 6th International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2013 |
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Country/Territory | Luxembourg |
City | Luxembourg |
Period | 18/03/13 → 20/03/13 |
Keywords
- Feature Models
- Mutation
- Similarity
- Software Product Lines
- Testing