Lazy model checking for recursive state machines

IF 2 3区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING Software and Systems Modeling Pub Date : 2024-03-20 DOI:10.1007/s10270-024-01159-z
Clemens Dubslaff, Patrick Wienhöft, Ansgar Fehnker
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Abstract

Recursive state machines (RSMs) are state-based models for procedural programs with wide-ranging applications in program verification and interprocedural analysis. Model-checking algorithms for RSMs and related formalisms have been intensively studied in the literature. In this article, we devise a new model-checking algorithm for RSMs and requirements in computation tree logic (CTL) that exploits the compositional structure of RSMs by ternary model checking in combination with a lazy evaluation scheme. Specifically, a procedural component is only analyzed in those cases in which it might influence the satisfaction of the CTL requirement. We implemented our model-checking algorithms and evaluate them on randomized scalability benchmarks and on an interprocedural data-flow analysis of Java programs, showing both practical applicability and significant speedups in comparison to state-of-the-art model-checking tools for procedural programs.

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递归状态机的懒模型检查
递归状态机(RSM)是基于状态的过程式程序模型,在程序验证和过程间分析中有着广泛的应用。文献中对 RSM 及相关形式主义的模型检查算法进行了深入研究。在本文中,我们为计算树逻辑(CTL)中的 RSM 和需求设计了一种新的模型检查算法,该算法通过三元模型检查结合懒评估方案利用了 RSM 的组成结构。具体来说,只有在程序组件可能影响 CTL 需求满足的情况下,才会对其进行分析。我们实现了我们的模型检查算法,并在随机可扩展性基准和 Java 程序的程序间数据流分析中对其进行了评估,结果表明,与最先进的程序模型检查工具相比,我们的算法不仅实用,而且速度明显加快。
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来源期刊
Software and Systems Modeling
Software and Systems Modeling 工程技术-计算机:软件工程
CiteScore
6.00
自引率
20.00%
发文量
104
审稿时长
>12 weeks
期刊介绍: We invite authors to submit papers that discuss and analyze research challenges and experiences pertaining to software and system modeling languages, techniques, tools, practices and other facets. The following are some of the topic areas that are of special interest, but the journal publishes on a wide range of software and systems modeling concerns: Domain-specific models and modeling standards; Model-based testing techniques; Model-based simulation techniques; Formal syntax and semantics of modeling languages such as the UML; Rigorous model-based analysis; Model composition, refinement and transformation; Software Language Engineering; Modeling Languages in Science and Engineering; Language Adaptation and Composition; Metamodeling techniques; Measuring quality of models and languages; Ontological approaches to model engineering; Generating test and code artifacts from models; Model synthesis; Methodology; Model development tool environments; Modeling Cyberphysical Systems; Data intensive modeling; Derivation of explicit models from data; Case studies and experience reports with significant modeling lessons learned; Comparative analyses of modeling languages and techniques; Scientific assessment of modeling practices
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