Ziniu Chen

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Pattern-based software failure detection is an important topic of research in recent years. In this method, a set of patterns from program execution traces are extracted, and represented as features, while their occurrence frequencies are treated as the corresponding feature values. But this conventional method has its limitation due to neglect the(More)
In this paper, we present a novel approach to software failure detection based on pattern position distributions as features. In this approach, we divide an execution sequence into several sections and then compute a pattern distribution in each section. The distribution of all patterns is then used as a feature to train a classifier. This approach(More)
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