A Randomized Scheduler with Probabilistic Guarantees of Finding Bugs

This paper presents a randomized scheduler for finding concurrency

bugs. Like current stress-testing methods, it repeatedly runs a

given test program with supplied inputs. However, it improves on

stress-testing by finding buggy schedules more effectively and by

quantifying the probability of missing concurrency bugs. Key to its

design is the characterization of the depth of a concurrency bug as

the minimum number of scheduling constraints required to find it. In

a single run of a program with $n$ threads and $k$ steps, our

scheduler detects a concurrency bug of depth $d$ with probability at

least $1/{nk^{d-1}}$. We hypothesize that in practice, many

concurrency bugs (including well-known types such as ordering

errors, atomicity violations, and deadlocks) have small bug-depths,

and we confirm the efficiency of our schedule randomization by

detecting previously unknown and known concurrency bugs in several

production-scale concurrent programs.

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In  Proceedings of the Fifteenth International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS 2010)

Publisher  Association for Computing Machinery, Inc.
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sebastian burckhardt, Pravesh Kothari, Madanlal Musuvathi, and Santosh Nagarakatte. A Randomized Scheduler with Probabilistic Guarantees of Finding Bugs, January 2010.

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