Cooperative empirical failure avoidance for multithreaded programs

Abstract

Concurrency errors in multithreaded programs are difficult to find and fix. We propose Aviso, a system for avoiding schedule-dependent failures. Aviso monitors events during a program's execution and, when a failure occurs, records a history of events from the failing execution. It uses this history to generate schedule constraints that perturb the order of events in the execution and thereby avoids schedules that lead to failures in future program executions. Aviso leverages scenarios where many instances of the same software run, using a statistical model of program behavior and experimentation to determine which constraints most effectively avoid failures. After implementing Aviso, we showed that it decreased failure rates for a variety of important desktop, server, and cloud applications by orders of magnitude, with an average overhead of less than 20% and, in some cases, as low as 5%.