Static Analysis of Runtime Errors in Interrupt-Driven Programs via Sequentialization

Author:

Wu Xueguang1,Chen Liqian1,Miné Antoine2,Dong Wei1,Wang Ji1

Affiliation:

1. National University of Defense Technology, Changsha, China

2. Université Pierre et Marie Curie, Paris Cedex, France

Abstract

Embedded software often involves intensive numerical computations and suffers from a number of runtime errors. The technique of numerical static analysis is of practical importance for checking the correctness of embedded software. However, most of the existing approaches of numerical static analysis consider sequential programs, while interrupts are a commonly used facility that introduces concurrency in embedded systems. Therefore, a numerical static analysis approach is highly desired for embedded software with interrupts. In this article, we propose a static analysis approach specifically for interrupt-driven programs based on sequentialization techniques. We present a method to sequentialize interrupt-driven programs into nondeterministic sequential programs according to the semantics of interrupts. The key benefit of using sequentialization is the ability to leverage the power of state-of-the-art analysis and verification techniques for sequential programs to analyze interrupt-driven programs, for example, the power of numerical abstract interpretation to analyze numerical properties of the sequentialized programs. Furthermore, to improve the analysis precision and scalability, we design specific abstract domains to analyze sequentialized interrupt-driven programs by considering their specific features. Finally, we present encouraging experimental results obtained by our prototype implementation.

Funder

973 Program

NSFC

Publisher

Association for Computing Machinery (ACM)

Subject

Hardware and Architecture,Software

Cited by 6 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. Detecting High Floating-Point Errors via Ranking Analysis;2022 29th Asia-Pacific Software Engineering Conference (APSEC);2022-12

2. Program Verification Enhanced Precise Analysis of Interrupt-Driven Program Vulnerabilities;2021 28th Asia-Pacific Software Engineering Conference (APSEC);2021-12

3. Rchecker: A CBMC-based Data Race Detector for Interrupt-driven Programs;2020 IEEE 20th International Conference on Software Quality, Reliability and Security Companion (QRS-C);2020-12

4. Research on SVM environment performance of parallel computing based on large data set of machine learning;The Journal of Supercomputing;2019-06-21

5. Analyzing Interrupt Handlers via Interprocedural Summaries;Lecture Notes in Computer Science;2018

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