Static Analysis and Stochastic Search for Reachability Problem

Q3 Computer Science
Xinwei Chai, Tony Ribeiro, Morgan Magnin, Olivier Roux , Katsumi Inoue
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引用次数: 1

Abstract

This paper focuses on a major improvement on the analysis of reachability properties in large-scale dynamical biological models. To tackle such models, where classical model checkers fail due to state space explosion led by exhaustive search. Alternative static analysis approaches have been proposed, but they may also fail in certain cases due to non-exhaustive search. In this paper, we introduce a hybrid approach ASPReach, which combines static analysis and stochastic search to break the limits of both approaches. We tackle this issue on a modeling framework we recently introduced, Asynchronous Binary Automata Network (ABAN). We show that ASPReach is able to analyze efficiently some reachability properties which could not be solved by existing methods. We studied also various cases from biological literature, emphasizing the merits of our approach in terms of conclusiveness and performance.

可达性问题的静态分析与随机搜索
本文重点介绍了大尺度动态生物模型中可达性分析的重大改进。为了解决这样的模型,经典模型检查器由于穷举搜索导致的状态空间爆炸而失败。已经提出了其他静态分析方法,但是由于非穷举搜索,它们也可能在某些情况下失败。在本文中,我们引入了一种混合方法as布道,它结合了静态分析和随机搜索来打破这两种方法的局限性。我们在最近介绍的一个建模框架——异步二进制自动机网络(ABAN)上解决了这个问题。结果表明,该方法能够有效地分析现有方法无法解决的一些可达性特性。我们还研究了生物学文献中的各种案例,强调了我们的方法在结论性和性能方面的优点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Electronic Notes in Theoretical Computer Science
Electronic Notes in Theoretical Computer Science Computer Science-Computer Science (all)
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