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The Case for Feature-Aware Similarity Measures in Software Product Line Testing

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  • Safwan Abd Razak

    (Faculty of Information and Communication Technology, Universiti Teknikal Malaysia, Malaysia)

  • Muhammad Fuad Abdullah

    (Faculty of Information and Communication Technology, Universiti Teknikal Malaysia, Malaysia)

  • Muhammad Shahkhir Mozamir

    (Faculty of Information and Communication Technology, Universiti Teknikal Malaysia, Malaysia)

  • Muhammad Huzaifah Ismail

    (Faculty of Information and Communication Technology, Universiti Teknikal Malaysia, Malaysia)

  • Muhammad Faheem Mohd Ezani

    (Faculty of Information and Communication Technology, Universiti Teknikal Malaysia, Malaysia)

Abstract

Traditional similarity distance measures (Jaccard, Hamming, Counting Function, Sorensen Dice) in SPL testing treat all features equally, ignoring the fundamental distinction between mandatory and optional features in feature models. This oversight leads to suboptimal test case prioritization and reduces fault detection efficiency. The primary objective is to demonstrate that traditional distance metrics, by treating all features equally, often fail to prioritize test cases that cover the most critical parts of an SPL, including those features that are present in all product variants.

Suggested Citation

  • Safwan Abd Razak & Muhammad Fuad Abdullah & Muhammad Shahkhir Mozamir & Muhammad Huzaifah Ismail & Muhammad Faheem Mohd Ezani, 2025. "The Case for Feature-Aware Similarity Measures in Software Product Line Testing," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 9(8), pages 4670-4681, August.
    • Handle: RePEc:bcp:journl:v:9:y:2025:issue-8:p:4670-4681
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