We experimentally evaluate the egectiveness of using cluster analpis of execution profiles to find failures among the executions induced by a set of potential test cases. We compare several filtering procedures for selecting executions to evaluate for conformance to requirements.Each filtering procedure involves a choice of a sampling strategy and a clustering metric. The results suggest that Jltering procedures based on clustering are more efective than simple random sampling for identibing failures in populations of operational executions, with adaptive sampling from clusters being the most effective sampling strategy. The results also suggest that clustering metrics that give extra weight to unusual profile features are most eflective. Scatter plots of execution populations, produced by multidimensional scaling, are used to provide intuition for these results.

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RuDRA, R. P. 1988

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