Lightweight Static Analysis for Data Race Detection in Operating System Kernels.

Authors

Andrianov Pavel, Khoroshilov Alexey, Mutilin Vadim

Abstract

The paper presents an approach to lightweight static data race detection. It takes into account the specifics of operating system kernels, such as complex parallelism and kernel specifics synchronization mechanisms. The method is based on the Lockset one, but it implements two heuristics that are aimed to reduce amount of false alarms: a memory model and a model of parallelism. The main target of our research and evaluation is operating system kernels but the approach can be applied to the other programs as well.

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Keywords

static analysis, data race, operating system kernel, shared data

Edition

Proceedings of TMPA-2014, pp.128-135, November 14-15, 2014, Kostroma, Russia.

Research Group

Software Engineering

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