Partial order reduction for event-driven multi-threaded programs

Abstract

Event-driven multi-threaded programming is fast becoming a preferred style of developing efficient and responsive applications. In this concurrency model, multiple threads execute concurrently, communicating through shared objects as well as by posting asynchronous events. In this work, we consider partial order reduction (POR) for this concurrency model. Existing POR techniques treat event queues associated with threads as shared objects and reorder every pair of events handled on the same thread even if reordering them does not lead to different states. We do not treat event queues as shared objects and propose a new POR technique based on a backtracking set called the dependence-covering set. Our POR technique reorders events handled by the same thread only if necessary. We prove that exploring dependence-covering sets suffices to detect all deadlock cycles and assertion violations defined over local variables. To evaluate effectiveness of our POR scheme, we have implemented a dynamic algorithm to compute dependence-covering sets. On execution traces of some Android applications, we demonstrate that our technique explores many fewer transitions —often orders of magnitude fewer— compared to exploration based on persistent sets, in which event queues are considered as shared objects.