ScaleCheck: A Single-Machine Approach for Discovering Scalability Bugs in Large Distributed Systems

Authors: 

Cesar A. Stuardo, University of Chicago; Tanakorn Leesatapornwongsa, Samsung Research America; Riza O. Suminto, Huan Ke, and Jeffrey F. Lukman, University of Chicago; Wei-Chiu Chuang, Cloudera; Shan Lu and Haryadi S. Gunawi, University of Chicago

Abstract: 

We present ScaleCheck, an approach for discovering scalability bugs (a new class of bug in large storage systems) and for democratizing large-scale testing. ScaleCheck employs a program analysis technique, for finding potential causes of scalability bugs, and a series of colocation techniques, for testing implementation code at real scales but doing so on just a commodity PC. ScaleCheck has been integrated to several large-scale storage systems, Cassandra, HDFS, Riak, and Voldemort, and successfully exposed known and unknown scalability bugs, up to 512-node scale on a 16-core PC.

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BibTeX
@inproceedings {227814,
author = {Cesar A. Stuardo and Tanakorn Leesatapornwongsa and Riza O. Suminto and Huan Ke and Jeffrey F. Lukman and Wei-Chiu Chuang and Shan Lu and Haryadi S. Gunawi},
title = {ScaleCheck: A Single-Machine Approach for Discovering Scalability Bugs in Large Distributed Systems},
booktitle = {17th {USENIX} Conference on File and Storage Technologies ({FAST} 19)},
year = {2019},
isbn = {978-1-931971-48-5},
address = {Boston, MA},
pages = {359--373},
url = {https://www.usenix.org/conference/fast19/presentation/stuardo},
publisher = {{USENIX} Association},
}