CrystalBall: Predicting and Preventing Inconsistencies in Deployed Distributed Systems

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CrystalBall: Predicting and Preventing Inconsistencies in Deployed Distributed Systems

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by Maysam Yabandeh , Dejan Kostić , Viktor Kuncak, et al.

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BibTeX

@MISC{Yabandeh_crystalball:predicting,
    author = {Maysam Yabandeh and Dejan Kostić and Viktor Kuncak and et al.},
    title = {CrystalBall: Predicting and Preventing Inconsistencies in Deployed Distributed Systems},
    year = {}
}

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Abstract

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 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.

Keyphrases

deployed distributed system new bug possible future violation related chain state exploration algorithm system implementation consequence prediction new approach property violation specified safety property distributed consequence distributed system inconsistent state system development new state exploration algorithm mature mace implementation recent consistent snapshot

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