TY - GEN
T1 - Test Coverage for Network Configurations
AU - Xu, Xieyang
AU - Deng, Weixin
AU - Beckett, Ryan
AU - Walker, David
N1 - Funding Information: We thank the NSDI’23 reviewers and our shepherd, Aditya Akella, for feedback on the earlier version of this paper. This work was supported in part by NSF grant CNS-2007073 and Cisco Systems. Publisher Copyright: © NSDI 2023.All rights reserved
PY - 2023
Y1 - 2023
N2 - We develop NetCov, the first tool to reveal which network configuration lines are tested by a suite of network tests. It helps network engineers improve test suites and thus increase network reliability. A key challenge in developing a tool like NetCov is that many network tests test the data plane instead of testing the configurations (control plane) directly. We must be able to efficiently infer which configuration elements contribute to tested data plane elements, even when such contributions are non-local (on remote devices) or non-deterministic. NetCov uses an information flow graph based model that precisely captures various forms of contributions and a scalable method to infer contributions. Using NetCov, we show that an existing test suite for Internet2, a nation-wide backbone network in the USA, covers only 26% of the configuration lines. The feedback from NetCov makes it easy to define new tests that improve coverage. For Internet2, adding just three such tests covers an additional 17% of the lines.
AB - We develop NetCov, the first tool to reveal which network configuration lines are tested by a suite of network tests. It helps network engineers improve test suites and thus increase network reliability. A key challenge in developing a tool like NetCov is that many network tests test the data plane instead of testing the configurations (control plane) directly. We must be able to efficiently infer which configuration elements contribute to tested data plane elements, even when such contributions are non-local (on remote devices) or non-deterministic. NetCov uses an information flow graph based model that precisely captures various forms of contributions and a scalable method to infer contributions. Using NetCov, we show that an existing test suite for Internet2, a nation-wide backbone network in the USA, covers only 26% of the configuration lines. The feedback from NetCov makes it easy to define new tests that improve coverage. For Internet2, adding just three such tests covers an additional 17% of the lines.
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M3 - Conference contribution
T3 - Proceedings of the 20th USENIX Symposium on Networked Systems Design and Implementation, NSDI 2023
SP - 1717
EP - 1732
BT - Proceedings of the 20th USENIX Symposium on Networked Systems Design and Implementation, NSDI 2023
PB - USENIX Association
T2 - 20th USENIX Symposium on Networked Systems Design and Implementation, NSDI 2023
Y2 - 17 April 2023 through 19 April 2023
ER -