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Predicting and Preventing Inconsistencies in Deployed Distributed Systems
EPFL.ORCID iD: 0000-0002-1256-1070
2010 (English)In: ACM Transactions on Computer Systems, ISSN 0734-2071, E-ISSN 1557-7333, Vol. 28, no 1Article in journal (Refereed) Published
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 article describes the design and 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 runtime.

Place, publisher, year, edition, pages
Association for Computing Machinery (ACM), 2010. Vol. 28, no 1
Keyword [en]
Experimentation; Reliability; Distributed systems; consequence prediction; reliability; execution steering; enforcing safety properties; Model Checking
National Category
Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-147097DOI: 10.1145/1731060.1731062ISI: 000276381600002Scopus ID: 2-s2.0-77950808422OAI: oai:DiVA.org:kth-147097DiVA: diva2:727663
Note

Qc 20140702

Available from: 2014-06-23 Created: 2014-06-23 Last updated: 2017-12-05Bibliographically approved

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Kostic, Dejan

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CiteExportLink to record
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  • apa
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