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Persuasive Prediction of Concurrency Access Anomalies
| Citations: | 10 - 3 self |
BibTeX
@MISC{Huang_persuasiveprediction,
author = {Jeff Huang and Charles Zhang},
title = {Persuasive Prediction of Concurrency Access Anomalies},
year = {}
}
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Abstract
Predictive analysis is a powerful technique that exposes concurrency bugs in un-exercised program executions. However, current predictive analysis approaches lack the persuasiveness property as they offer little assistance in helping programmers fully understand the execution history that triggers the predicted bugs. We present a persuasive bug prediction technique as well as a prototype tool, PECAN, for detecting general access anomalies (AAs) in concurrent programs. The main characteristic of PECAN is that, in addition to predict AAs in a more general way, it generates “bug hatching clips ” that deterministically instruct the input program to exercise the predicted AAs. The key ingredient of PECAN is an efficient offline schedule generation algorithm, with proof of the soundness, that guarantees to generate a feasible schedule for every real AA in programs that use locks in a nested way. We evaluate PECAN using twenty-two multi-threaded subjects including six large concurrent systems, and our experiments demonstrate that PECAN is able to effectively predict and deterministically expose real AAs. Several serious and previously unknown bugs in large open source concurrent systems were also revealed in our experiments.
Keyphrases
persuasive prediction concurrency access anomaly predictive analysis concurrency bug twenty-two multi-threaded subject input program predicted bug large concurrent system nested way persuasive bug prediction technique large open source concurrent system persuasiveness property general way real aa un-exercised program execution unknown bug concurrent program general access anomaly prototype tool feasible schedule key ingredient efficient offline schedule generation algorithm expose real aa little assistance current predictive analysis approach main characteristic execution history predicted aa powerful technique
