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Spectrum-Based Fault Localization in Software Product Lines.pdf (360.1Kb)
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Title
Spectrum-based fault localization in software product lines
Author
Arrieta, Aitor
Etxeberria, Leire
Markiegi, Urtzi
Sagardui, Goiuria
Author (from another institution)
Segura, Sergio
Research Group
Ingeniería del software y sistemas
Version
Postprint
Rights
© 2018 Elsevier B. V.
Access
Embargoed access
URI
https://hdl.handle.net/20.500.11984/1133
Publisher’s version
https://doi.org/10.1016/j.infsof.2018.03.008
Published at
Information and Software Technology  Vol. 100. Pp. 18-31. August,
xmlui.dri2xhtml.METS-1.0.item-publicationfirstpage
18
xmlui.dri2xhtml.METS-1.0.item-publicationlastpage
31
Publisher
Elsevier B. V.
Keywords
Software product lines
Sprectum-based fault localization
Feature models
Debugging
Abstract
Context: Software Product Line (SPL) testing is challenging mainly due to the potentially huge number of products under test. Most of the research on this field focuses on making testing affordable ... [+]
Context: Software Product Line (SPL) testing is challenging mainly due to the potentially huge number of products under test. Most of the research on this field focuses on making testing affordable by selecting a representative subset of products to be tested. However, once the tests are executed and some failures revealed, debugging is a cumbersome and time consuming task due to difficulty to localize and isolate the faulty features in the SPL. Objective: This paper presents a debugging approach for the localization of bugs in SPLs. Method: The proposed approach works in two steps. First, the features of the SPL are ranked according to their suspiciousness (i.e., likelihood of being faulty) using spectrum-based localization techniques. Then, a novel fault isolation approach is used to generate valid products of minimum size containing the most suspicious features, helping to isolate the cause of failures. Results: For the evaluation of our approach, we compared ten suspiciousness techniques on nine SPLs of different sizes. The results reveal that three of the techniques (Tarantula, Kulcynski2 and Ample2) stand out over the rest, showing a stable performance with different types of faults and product suite sizes. By using these metrics, faults were localized by examining between 0.1% and 14.4% of the feature sets. Conclusion: Our results show that the proposed approach is effective at locating bugs in SPLs, serving as a helpful complement for the numerous approaches for testing SPLs [-]
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