Test Coverage for Network Configurations

TL;DR

NetCov is a novel tool that identifies which network configuration lines are tested by network tests, helping engineers improve test coverage and network reliability through an information flow graph model.

Contribution

It introduces NetCov, the first tool to efficiently infer configuration testing coverage in networks, including non-local and non-deterministic contributions.

Findings

Existing test suite covers only 26% of configuration lines.

Adding three new tests increases coverage by 17%.

NetCov enables targeted test improvements for better network reliability.

Abstract

We develop NetCov, the first tool to reveal which network configuration lines are being tested by a suite of network tests. It helps network engineers improve test suites and thus increase network reliability. A key challenge in its development 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 lazily infer contributions. Using it, 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.