Feature location benchmark for extractive software product line adoption research using realistic and synthetic Eclipse variants - Sorbonne Université
Article Dans Une Revue Information and Software Technology Année : 2018

Feature location benchmark for extractive software product line adoption research using realistic and synthetic Eclipse variants

Résumé

Context: It is common belief that high impact research in software reuse requires assessment in non-trivial, comparable, and reproducible settings. However, software artefacts and common representations are usually unavailable. Also, establishing a representative ground truth is a challenging and debatable subject. Feature location in the context of software families, which is key for software product line adoption, is a research field that is becoming more mature with a high proliferation of techniques. Objective: We present EFLBench, a benchmark and a framework to provide a common ground for the evaluation of feature location techniques in families of systems. Method: EFLBench leverages the efforts made by the Eclipse Community which provides feature-based family artefacts and their plugin-based implementations. Eclipse is an active and non-trivial project and thus, it establishes an unbiased ground truth which is realistic and challenging. Results: EFLBench is publicly available and supports all tasks for feature location techniques integration, benchmark construction and benchmark usage. We demonstrate its usage, simplicity and reproducibility by comparing four techniques in Eclipse releases. As an extension of our previously published work, we consider a decade of Eclipse releases and we also contribute an approach to automatically generate synthetic Eclipse variants to benchmark feature location techniques in tailored settings. We present and discuss three strategies for this automatic generation and we present the results using different settings. Conclusion: EFLBench is a contribution to foster the research in feature location in families of systems providing a common framework and a set of baseline techniques and results.
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Dates et versions

hal-01871155 , version 1 (10-09-2018)

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Jabier F Martinez, Tewfik Ziadi, Mike Papadakis, Tegawendé F. Bissyandé, Jacques Klein, et al.. Feature location benchmark for extractive software product line adoption research using realistic and synthetic Eclipse variants. Information and Software Technology, 2018, ⟨10.1016/j.infsof.2018.07.005⟩. ⟨hal-01871155⟩
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