BigBug: Practical concurrency analysis for SDN
Abstract
By operating in highly asynchronous environments, SDN controllers often suffer from bugs caused by concurrency violations. Unfortunately, state-of-the-art concurrency analyzers for SDNs often report thousands of true violations, limiting their effectiveness in practice.
This paper presents BigBug, an approach for automatically identifying the most representative concurrency violations: those that capture the cause of the violation. The two key insights behind BigBug are that: (i) many violations share the same root cause, and (ii) violations with the same cause share common characteristics. BigBug leverages these observations to cluster reported violations according to the similarity of events in them as well as SDN-specific features. BigBug then reports the most representative violation for each cluster using a ranking function.
We implemented BigBug and showed its practical effectiveness. In more than 100 experiments involving different controllers and applications, BigBug systematically produced 6 clusters or less, corresponding to a median decrease of 95% over state-of-the-art analyzers. The number of violations reported by BigBug also closely matched that of actual bugs, indicating that BigBug is effective at identifying root causes of SDN races.
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BibTex
@INPROCEEDINGS{may2017bigbug,
isbn = {978-1-4503-4947-5},
doi = {10.1145/3050220.3050230},
year = {2017},
booktitle = {SOSR '17: Proceedings of the Symposium on SDN Research},
type = {Conference Paper},
author = {May, Roman and El-Hassany, Ahmed and Vanbever, Laurent and Vechev, Martin},
keywords = {Software Defined Networking; OpenFlow; Commutativity Specification; Happens-before; Nondeterminism},
language = {en},
address = {New York, NY},
publisher = {Association for Computing Machinery},
title = {BigBug: Practical concurrency analysis for SDN},
PAGES = {88 - 94},
Note = {Symposium on SDN Research (SOSR '17); Conference Location: Santa Clara, CA, USA; Conference Date: April 3-4, 2017}
}Research Collection: 20.500.11850/192033