Code Coverage Measurement in Configurable Software Product Line Testing


KIPS Transactions on Software and Data Engineering, Vol. 11, No. 7, pp. 273-282, Jul. 2022
https://doi.org/10.3745/KTSDE.2022.11.7.273,   PDF Download:
Keywords: Configurable Software Product Line, Software Product Line Testing, Test Coverage Measurement, Code Coverage
Abstract

Testing approaches for configurable software product lines differs significantly from a single software testing, as it requires consideration of common parts used by all member products of a product line and variable parts shared by some or a single product. Test coverage is a measure of the adequacy of testing performed. Test coverage measurements are important to evaluate the adequacy of testing at the software product line level, as there can be hundreds of member products produced from configurable software product lines. This paper proposes a method for measuring code coverage at the product line level in configurable software product lines. The proposed method tests the member products of a product line after hierarchizing member products based on the inclusion relationship of the selected features, and quantifies SPL(Software Product Line) test coverage by synthesizing the test coverage of each product. As a result of applying the proposed method to 11 configurable software product line cases, we confirmed that the proposed method could quantitatively visualize how thoroughly the SPL testing was performed to help verify the adequacy of the SPL testing. In addition, we could check whether the newly performed testing for a member product covers the newly added code parts of a feature.


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Cite this article
[IEEE Style]
S. Han, J. Lee and S. Go, "Code Coverage Measurement in Configurable Software Product Line Testing," KIPS Transactions on Software and Data Engineering, vol. 11, no. 7, pp. 273-282, 2022. DOI: https://doi.org/10.3745/KTSDE.2022.11.7.273.

[ACM Style]
Soobin Han, Jihyun Lee, and Seoyeon Go. 2022. Code Coverage Measurement in Configurable Software Product Line Testing. KIPS Transactions on Software and Data Engineering, 11, 7, (2022), 273-282. DOI: https://doi.org/10.3745/KTSDE.2022.11.7.273.