Predicting and Preventing Inconsistencies in Deployed Distributed Systems
2010 (English)In: ACM Transactions on Computer Systems, ISSN 0734-2071, Vol. 28, no 1Article in journal (Refereed) Published
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
Experimentation; Reliability; Distributed systems; consequence prediction; reliability; execution steering; enforcing safety properties; Model Checking
IdentifiersURN: urn:nbn:se:kth:diva-147097DOI: 10.1145/1731060.1731062ISI: 000276381600002ScopusID: 2-s2.0-77950808422OAI: oai:DiVA.org:kth-147097DiVA: diva2:727663
Qc 201407022014-06-232014-06-232014-07-02Bibliographically approved