DRDDR: a lightweight method to detect data races in Linux kernel

Abstract

Data races in parallel programs are notoriously difficult to detect and resolve. Existing research has mostly focused on data race detection at the user level and significant progress has been made in this regard. However, a very few efforts have attempted to address OS kernel level races. In contrast to user-level applications, the code in kernels uses vastly more complicated synchronization mechanisms, including different kinds of locks, hardware and software interrupts, widely used signal/wait primitives, and various types of low-level shared resources. It is therefore difficult to apply detection methods designed for user-level applications to identify OS kernel level races. In this paper, we present a new detection tool that is able to effectively detect race conditions in the Linux kernel environment. We use a dynamic detection approach, employing hardware debug registers available on commodity processors, to catch races on the fly during runtime. Preliminary experimental results show that our tool can effectively identify real data race instances.