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research article

Predicting and Preventing Inconsistencies in Deployed Distributed Systems

Yabandeh, Maysam  
•
Knezevic, Nikola
•
Kostic, Dejan  
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2010
ACM Transactions on Computer Systems

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.

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Type
research article
DOI
10.1145/1731060.1731062
Web of Science ID

WOS:000276381600002

Author(s)
Yabandeh, Maysam  
•
Knezevic, Nikola
•
Kostic, Dejan  
•
Kuncak, Viktor  
Date Issued

2010

Publisher

Association for Computing Machinery

Published in
ACM Transactions on Computer Systems
Volume

28

Issue

1

Start page

2

Subjects

Experimentation

•

Reliability

•

Distributed systems

•

consequence prediction

•

reliability

•

execution steering

•

enforcing safety properties

•

Model Checking

Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
NSL  
LARA  
Available on Infoscience
January 11, 2010
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/45459
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