Methods for Efficient Unfolding of Colored Petri Nets

IF 0.4 4区 计算机科学 Q4 COMPUTER SCIENCE, SOFTWARE ENGINEERING Fundamenta Informaticae Pub Date : 2023-10-26 DOI:10.3233/fi-222162
Alexander Bilgram, Peter G. Jensen, Thomas Pedersen, Jiří Srba, Peter H. Taankvist
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Abstract

Colored Petri nets offer a compact and user friendly representation of the traditional Place/Transition (P/T) nets and colored nets with finite color ranges can be unfolded into the underlying P/T nets, however, at the expense of an exponential explosion in size. We present two novel techniques based on static analysis in order to reduce the size of unfolded colored nets. The first method identifies colors that behave equivalently and groups them into equivalence classes, potentially reducing the number of used colors. The second method overapproximates the sets of colors that can appear in places and excludes colors that can never be present in a given place. Both methods are complementary and the combined approach allows us to significantly reduce the size of multiple colored Petri nets from the Model Checking Contest benchmark. We compare the performance of our unfolder with state-of-the-art techniques implemented in the tools MCC, Spike and ITS-Tools, and while our approach is competitive w.r.t. unfolding time, it also outperforms the existing approaches both in the size of unfolded nets as well as in the number of answered model checking queries from the 2021 Model Checking Contest.
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彩色Petri网的有效展开方法
彩色Petri网提供了传统的位置/过渡(P/T)网的紧凑和用户友好的表示,具有有限颜色范围的彩色网可以展开为潜在的P/T网,然而,代价是尺寸呈指数级爆炸。为了减小未展开的彩色网的尺寸,我们提出了两种基于静态分析的新技术。第一种方法识别行为相同的颜色,并将它们分组到等价类中,这可能会减少使用颜色的数量。第二种方法过于接近可能出现在某个地方的颜色集,而排除了永远不可能出现在给定位置的颜色。这两种方法是互补的,组合方法使我们能够从模型检查竞赛基准中显着减少多个彩色Petri网的大小。我们将我们的解文件夹性能与MCC、Spike和ITS-Tools工具中实现的最先进技术进行了比较,虽然我们的方法在展开时间上具有竞争力,但在展开网络的大小以及2021年模型检查竞赛中回答的模型检查查询的数量方面,它也优于现有方法。
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来源期刊
Fundamenta Informaticae
Fundamenta Informaticae 工程技术-计算机:软件工程
CiteScore
2.00
自引率
0.00%
发文量
61
审稿时长
9.8 months
期刊介绍: Fundamenta Informaticae is an international journal publishing original research results in all areas of theoretical computer science. Papers are encouraged contributing: solutions by mathematical methods of problems emerging in computer science solutions of mathematical problems inspired by computer science. Topics of interest include (but are not restricted to): theory of computing, complexity theory, algorithms and data structures, computational aspects of combinatorics and graph theory, programming language theory, theoretical aspects of programming languages, computer-aided verification, computer science logic, database theory, logic programming, automated deduction, formal languages and automata theory, concurrency and distributed computing, cryptography and security, theoretical issues in artificial intelligence, machine learning, pattern recognition, algorithmic game theory, bioinformatics and computational biology, quantum computing, probabilistic methods, algebraic and categorical methods.
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