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Automatic Detection, Validation and Repair of Race Conditions in Interrupt-Driven Embedded Software

Authors :
Wang, Yu
Gao, Fengjuan
Wang, Linzhang
Yu, Tingting
Wang, Ke
Zhao, Jianhua
Li, Xuandong
Publication Year :
2023

Abstract

Interrupt-driven programs are widely deployed in safety-critical embedded systems to perform hardware and resource dependent data operation tasks. The frequent use of interrupts in these systems can cause race conditions to occur due to interactions between application tasks and interrupt handlers (or two interrupt handlers). Numerous program analysis and testing techniques have been proposed to detect races in multithreaded programs. Little work, however, has addressed race condition problems related to hardware interrupts. In this paper, we present SDRacer, an automated framework that can detect, validate and repair race conditions in interrupt-driven embedded software. It uses a combination of static analysis and symbolic execution to generate input data for exercising the potential races. It then employs virtual platforms to dynamically validate these races by forcing the interrupts to occur at the potential racing points. Finally, it provides repair candidates to eliminate the detected races. We evaluate SDRacer on nine real-world embedded programs written in C language. The results show that SDRacer can precisely detect and successfully fix race conditions.<br />Comment: This is a draft version of the published paper. Ke Wang provides suggestions for improving the paper and README of the GitHub repo

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2305.17869
Document Type :
Working Paper