Joan Farjo

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Researchers in the dynamic program analysis field have extensively used cluster analysis to address various problems. Typically, the clustering techniques are applied onto execution profiles having high dimensionality (i.e., involving a large number of profiling elements), sometimes in the order of thousands or even hundreds of thousands. Our concern is(More)
Researchers have applied cluster analysis onto execution profiles induced by test cases in order to solve problems in the area of software testing and analysis. The employed clustering techniques varied, and no study was conducted to rate these techniques in terms of their effectiveness in this specific domain. This work aims at doing so experimentally.(More)
Existing execution profiles comprise information about the execution of program elements such as statements, branches, and def-use pairs. They lack any information about what elements are potentially more relevant to failure than others, such information could be leveraged to compute dissimilarity metrics that discriminate better between failing and passing(More)
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