A DSL for Resource Checking Using Finite State Automaton-Driven Symbolic Execution

Author:

Fülöp Endre1,Pataki Norbert2

Affiliation:

1. Department of Programming Language and Compilers , Eötvös Loránd University

2. ELTE Eötvös Loránd University , Budapest , Hungary , Faculty of Informatics, 3in Research Group , Martonvásár , Hungary

Abstract

Abstract Static analysis is an essential way to find code smells and bugs. It checks the source code without execution and no test cases are required, therefore its cost is lower than testing. Moreover, static analysis can help in software engineering comprehensively, since static analysis can be used for the validation of code conventions, for measuring software complexity and for executing code refactorings as well. Symbolic execution is a static analysis method where the variables (e.g. input data) are interpreted with symbolic values. Clang Static Analyzer is a powerful symbolic execution engine based on the Clang compiler infrastructure that can be used with C, C++ and Objective-C. Validation of resources’ usage (e.g. files, memory) requires finite state automata (FSA) for modeling the state of resource (e.g. locked or acquired resource). In this paper, we argue for an approach in which automata are in-use during symbolic execution. The generic automaton can be customized for different resources. We present our domain-specific language to define automata in terms of syntactic and semantic rules. We have developed a tool for this approach which parses the automaton and generates Clang Static Analyzer checker that can be used in the symbolic execution engine. We show an example automaton in our domain-specific language and the usage of generated checker.

Publisher

Walter de Gruyter GmbH

Subject

General Computer Science

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Temporal Logic-driven Symbolic Execution with the Clang Static Analyzer;2024 7th International Conference on Software and System Engineering (ICoSSE);2024-04-19

2. Timed-SAS: Modeling and Analyzing the Time Behaviors of Self-Adaptive Software under Uncertainty;Applied Sciences;2023-02-03

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