约束角子句在程序验证中的分析与转换

IF 1.4 2区 数学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING Theory and Practice of Logic Programming Pub Date : 2021-08-02 DOI:10.1017/s1471068421000211
E. D. Angelis, F. Fioravanti, J. Gallagher, M. Hermenegildo, A. Pettorossi, M. Proietti
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引用次数: 15

摘要

本文综述了将约束逻辑编程(CLP)领域的分析和转换技术应用于软件系统验证问题的最新工作。我们提出了基于专门化的技术,用于将不同编程语言和一般软件系统的验证问题转换为约束Horn子句(CHCs)的可满足性问题,该术语在验证领域已流行,指的是CLP程序。然后,我们描述了可用于推断相关程序属性(如循环不变量)的chc的静态分析技术。我们还概述了一些基于专门化和折叠/展开规则的转换技术,这些技术有助于提高CHC满意度工具的有效性。最后,我们讨论了应用这些技术的未来发展。
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Analysis and Transformation of Constrained Horn Clauses for Program Verification
This paper surveys recent work on applying analysis and transformation techniques that originate in the field of constraint logic programming (CLP) to the problem of verifying software systems. We present specialization-based techniques for translating verification problems for different programming languages, and in general software systems, into satisfiability problems for constrained Horn clauses (CHCs), a term that has become popular in the verification field to refer to CLP programs. Then, we describe static analysis techniques for CHCs that may be used for inferring relevant program properties, such as loop invariants. We also give an overview of some transformation techniques based on specialization and fold/unfold rules, which are useful for improving the effectiveness of CHC satisfiability tools. Finally, we discuss future developments in applying these techniques.
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来源期刊
Theory and Practice of Logic Programming
Theory and Practice of Logic Programming 工程技术-计算机:理论方法
CiteScore
4.50
自引率
21.40%
发文量
40
审稿时长
>12 weeks
期刊介绍: Theory and Practice of Logic Programming emphasises both the theory and practice of logic programming. Logic programming applies to all areas of artificial intelligence and computer science and is fundamental to them. Among the topics covered are AI applications that use logic programming, logic programming methodologies, specification, analysis and verification of systems, inductive logic programming, multi-relational data mining, natural language processing, knowledge representation, non-monotonic reasoning, semantic web reasoning, databases, implementations and architectures and constraint logic programming.
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