Machine-Learning-Guided Selectively Unsound Static Analysis

We present a machine-learning-based technique for selectively applying unsoundness in static analysis. Existing bug-finding static analyzers are unsound in order to be precise and scalable in practice. However, they are uniformly unsound and hence at the risk of missing a large amount of real bugs....

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Vydané v:	Proceedings / International Conference on Software Engineering s. 519 - 529
Hlavní autori:	Kihong Heo, Oh, Hakjoo, Kwangkeun Yi
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 01.05.2017
Predmet:	Benchmark testing Bug-finding Computer bugs Libraries Machine Learning Scalability Software engineering Static Analysis Support vector machines
ISSN:	1558-1225
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