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        <dc:title>Comparing white-box and black-box test prioritization</dc:title>
        <dc:creator>Henard, C</dc:creator>
        <dc:creator>Papadakis, M</dc:creator>
        <dc:creator>Harman, M</dc:creator>
        <dc:creator>Jia, Y</dc:creator>
        <dc:creator>Traon, YL</dc:creator>
        <dc:description>Although white-box regression test prioritization has been well-studied, the more recently introduced black-box prioritization approaches have neither been compared against each other nor against more well-established white-box techniques. We present a comprehensive experimental comparison of several test prioritization techniques, including wellestablished white-box strategies and more recently introduced black-box approaches. We found that Combinatorial Interaction Testing and diversity-based techniques (Input Model Diversity and Input Test Set Diameter) perform best among the black-box approaches. Perhaps surprisingly, we found little difference between black-box and white-box performance (at most 4% fault detection rate difference). We also found the overlap between black-and white-box faults to be high: the first 10% of the prioritized test suites already agree on at least 60% of the faults found. These are positive findings for practicing regression testers who may not have source code available, thereby making white-box techniques inapplicable. We also found evidence that both black-box and white-box prioritization remain robust over multiple system releases.</dc:description>
        <dc:subject>Regression Testing, White-box, Black-box</dc:subject>
        <dc:publisher>Association for Computing Machinery (ACM)</dc:publisher>
        <dc:contributor>Dillon, L</dc:contributor>
        <dc:contributor>Visser, W</dc:contributor>
        <dc:contributor>Williams, L</dc:contributor>
        <dc:date>2016-05</dc:date>
        <dc:type>Proceedings paper</dc:type>
        <dc:language>eng</dc:language>
        <dc:source>     In: Dillon, L and Visser, W and Williams, L, (eds.) ICSE '16: Proceedings of the 38th International Conference on Software Engineering.  (pp. pp. 523-534).  Association for Computing Machinery (ACM): New York. (2016)     </dc:source>
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