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Refinement of structural heuristics for model checking of concurrent programs through data mining

机译:细化结构启发式方法,以通过数据挖掘对并发程序进行模型检查

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Detecting concurrency bugs in multi-threaded programs through model-checking is complicated by the combinatorial explosion in the number of ways that different threads can be interleaved to produce different combinations of behaviors. At the same time, concurrency bugs tend to be limited in their scope and scale due to the way in which concurrent programs are designed, and making visible the rules that govern the relationships between threads can help us to better identify which interleavings are worth investigating. In this work, patterns of read-write sequences are mined from a single execution of the target program to produce a quantitative, categorical model of thread behaviors. This model is exploited by a novel structural heuristic. Experiments with a proof-of-concept implementation, built using Java Pathfinder and WEKA, demonstrate that this heuristic locates bugs faster and more reliably than a conventional counterpart. (C) 2016 Elsevier Ltd. All rights reserved.
机译:通过模型检查来检测多线程程序中的并发性错误由于组合爆炸的复杂性而增加,可以通过多种方式交错不同的线程以产生不同的行为组合。同时,由于并发错误的设计和并发程序的方式,它们往往在范围和规模上受到限制,并且使控制线程之间关系的规则可见可以帮助我们更好地识别哪些交织值得研究。在这项工作中,从目标程序的单次执行中提取了读写序列的模式,以生成线程行为的定量分类模型。这种模型被一种新颖的结构启发法所利用。使用Java Pathfinder和WEKA构建的概念验证实现的实验表明,这种启发式方法比传统方法能够更快,更可靠地定位错误。 (C)2016 Elsevier Ltd.保留所有权利。

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