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CrystalBall: Predicting and Preventing Inconsistencies in Deployed Distributed Systems
EPFL.ORCID iD: 0000-0002-1256-1070
2009 (English)In: Proceedings of the 6th USENIX Symposium on Networked Systems Design and Implementation (NSDI ’09), 2009Conference paper (Refereed)
Abstract [en]

We propose a new approach for developing and deploying distributed systems, in which nodes predict distributed consequences of their actions, and use this information to detect and avoid errors. Each node continuously runs a state exploration algorithm on a recent consistent snapshot of its neighborhood and predicts possible future violations of specified safety properties. We describe a new state exploration algorithm, consequence prediction, which explores causally related chains of events that lead to property violation. This paper describes the design and the implementation of this approach, termed CrystalBall. We evaluate CrystalBall on RandTree, BulletPrime, Paxos, and Chord distributed system implementations. We identified new bugs in mature Mace implementations of three systems. Furthermore, we show that if the bug is not corrected during system development, CrystalBall is effective in steering the execution away from inconsistent states at run-time.

Place, publisher, year, edition, pages
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Computer Science
URN: urn:nbn:se:kth:diva-147092OAI: diva2:727655
The 6th USENIX Symposium on Networked Systems Design and Implementation (NSDI ’09)

QC 20140707

Available from: 2014-06-23 Created: 2014-06-23 Last updated: 2014-07-07Bibliographically approved

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Kostic, Dejan
Computer Science

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