Partial Orders for Precise and Efficient Dynamic Deadlock Prediction

TL;DR

This paper introduces a novel partial order method for dynamic deadlock prediction in concurrent programs, reducing false positives while maintaining detection accuracy.

Contribution

It proposes the TRW partial order approach, proven sound and complete under certain conditions, to improve deadlock prediction efficiency and accuracy.

Findings

TRW partial order is sound, avoiding false positives.

The approach is computationally efficient.

Both variants report the same deadlocks on benchmarks.

Abstract

Deadlocks are a major source of bugs in concurrent programs. They are hard to predict, because they may only occur under specific scheduling conditions. Dynamic analysis attempts to identify potential deadlocks by examining a single execution trace of the program. A standard approach involves monitoring sequences of lock acquisitions in each thread, with the goal of identifying deadlock patterns. A deadlock pattern is characterized by a cyclic chain of lock acquisitions, where each lock is held by one thread while being requested by the next. However, it is well known that not all deadlock patterns identified in this way correspond to true deadlocks, as they may be impossible to manifest under any schedule. We tackle this deficiency by proposing a new method based on partial orders to eliminate false positives: lock acquisitions must be unordered under a given partial order, and not preceded by other deadlock patterns. We prove soundness (no falsely predicted deadlocks) for the novel TRW partial order, and completeness (no deadlocks missed) for a slightly weakened variant of TRW. Both partial orders can be computed efficiently and report the same deadlocks for an extensive benchmark suite.