Efficient race detection in the presence of programmatic event loops

Abstract

An event loop is the basic scheduling mechanism for programs that respond to asynchronous events. In some frameworks, only the runtime can spin event loops, while in others, these can also be spun programmatically by event handlers. The latter provides more flexibility and helps improve responsiveness in cases where an event handler must wait for some input, for example, from the user or network. It can do so while spinning an event loop. In this paper, we consider the scheduling scheme of programmatic event loops. Programs which follow this scheme are prone to interference between a handler that is spinning an event loop and another handler that runs inside the loop. We present a happens-before based race detection technique for such programs. We exploit the structure and semantics of executions of these programs to design a sparse representation of the happens-before relation. It relates only a few pairs of operations explicitly in such a way that the ordering between any pair of operations can be inferred from the sparse representation in constant time. We have implemented our technique in an offline race detector for C/C++ programs, called SparseRacer. We discovered 13 new and harmful race conditions in 9 open-source applications using SparseRacer. So far, developers have confirmed 8 as valid bugs, and have fixed 3. These bugs arise from unintended interference due to programmatic event loops. Our sparse representation improved efficiency and gave an average speedup of 5x in race detection time.