FuseIC3: An algorithm for checking large design spaces

Rohit Dureja, Kristin Yvonne Rozier
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引用次数: 13

Abstract

The design of safety-critical systems often requires design space exploration: comparing several system models that differ in terms of design choices, capabilities, and implementations. Model checking can compare different models in such a set, however, it is continuously challenged by the state space explosion problem. Therefore, learning and reusing information from solving related models becomes very important for future checking efforts. For example, reusing variable ordering in BDD-based model checking leads to substantial performance improvement. In this paper, we present a SAT-based algorithm for checking a set of models. Our algorithm, FuseIC3, extends IC3 to minimize time spent in exploring the common state space between related models. Specifically, FuseIC3 accumulates artifacts from the sequence of over-approximated reachable states, called frames, from earlier runs when checking new models, albeit, after careful repair. It uses bidirectional reachability; forward reachability to repair frames, and IC3-type backward reachability to block predecessors to bad states. We extensively evaluate FuseIC3 over a large collection of challenging benchmarks. FuseIC3 is on-average up to 5.48× (median 1.75× ) faster than checking each model individually, and up to 3.67× (median 1.72×) faster than the state-of-the-art incremental IC3 algorithm.
FuseIC3:用于检查大型设计空间的算法
安全关键系统的设计通常需要设计空间探索:比较在设计选择、功能和实现方面不同的几个系统模型。模型校核可以对这样一个集合中的不同模型进行比较,但状态空间爆炸问题不断给模型校核带来挑战。因此,从求解相关模型中学习和重用信息对于未来的检查工作变得非常重要。例如,在基于bdd的模型检查中重用变量排序可以显著提高性能。在本文中,我们提出了一种基于sat的算法来检查一组模型。我们的算法FuseIC3扩展了IC3,以最小化在相关模型之间探索公共状态空间所花费的时间。具体来说,FuseIC3在检查新模型时(尽管经过仔细修复)从早期运行的过度逼近的可达状态序列(称为帧)中积累工件。它使用双向可达性;前向可达性用于修复帧,ic3类型的后向可达性用于阻止先前的坏状态。我们在大量具有挑战性的基准测试中广泛评估了FuseIC3。平均而言,FuseIC3比单独检查每个模型快5.48倍(中值1.75倍),比最先进的增量IC3算法快3.67倍(中值1.72倍)。
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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