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Track your project's code coverage over time, changes to files, and badge your GitHub repo
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What is Coveralls?

Coveralls works with your CI server and sifts through your coverage data to find issues you didn't even know you had before they become a problem. Free for open source, pro accounts for private repos, instant sign up with GitHub OAuth.
Coveralls is a tool in the Code Coverage category of a tech stack.

Who uses Coveralls?

78 companies reportedly use Coveralls in their tech stacks, including Kong, Practo, and Development.

195 developers on StackShare have stated that they use Coveralls.

Coveralls Integrations

Jenkins, Travis CI, CircleCI, Codeship, and Bitrise are some of the popular tools that integrate with Coveralls. Here's a list of all 6 tools that integrate with Coveralls.
Public Decisions about Coveralls

Here are some stack decisions, common use cases and reviews by companies and developers who chose Coveralls in their tech stack.

Tim Abbott
Tim Abbott
Shared insights

We use Codecov because it's a lot better than Coveralls. Both of them provide the useful feature of having nice web-accessible reports of which files have what level of test coverage (though every coverage tool produces reasonably nice HTML in a directory on the local filesystem), and can report on PRs cases where significant new code was added without test coverage.

That said, I'm pretty unhappy with both of them for our use case. The fundamental problem with both of them is that they don't handle the ~1% probability situations with missing data due to networking flakiness well. The reason I think our use case is relevant is that we submit coverage data from multiple jobs (one that runs our frontend test suite and another that runs our backend test suite), and the coverage provider is responsible for combining that data together.

I think the problem is if a test suite runs successfully but due to some operational/networking error between Travis/CircleCI and Codecov the coverage data for part of the codebase doesn't get submitted, Codecov will report a huge coverage drop in a way that is very confusing for our contributors (because they experience it as "why did the coverage drop 12%, all I did was added a test").

We migrated from Coveralls to Codecov because empirically this sort of breakage happened 10x less on Codecov, but it still happens way more often than I'd like.

I wish they put more effort in their retry mechanism and/or providing clearer debugging information (E.g. a big "Missing data" banner) so that one didn't need to be specifically told to ignore Codecov/Coveralls when it reports a giant coverage drop.

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Shared insights

Codecov Although I actually use both codecov and Coveralls, I very much like the graphs I get from codecov, and some of their diagnostic tools.

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Shared insights

Code Coverage is an important metric for us as we aim to deliver regular improvements to our platform. Coveralls

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Coveralls's Features

  • Repository Coverage Statistics
  • Individual File Coverage Reports
  • Line By Line Coverage
  • Repository Overview

Coveralls Alternatives & Comparisons

What are some alternatives to Coveralls?
A powerful and efficient Javascript framework that helps you build great apps. It is the fastest way to write scalable React/Redux with the least overhead.
Our patrons rave about our elegant coverage reports, integrated pull request comments, interactive commit graphs, our Chrome plugin and security.
SonarQube provides an overview of the overall health of your source code and even more importantly, it highlights issues found on new code. With a Quality Gate set on your project, you will simply fix the Leak and start mechanically improving.
Code coverage metric storage service. Provide coverage metrics on differentials with Phabricator and Jenkins, just like Coveralls does for GitHub and TravisCI.

Coveralls's Followers
234 developers follow Coveralls to keep up with related blogs and decisions.
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小械褉谐械泄 效械褉薪褘泄
James Kessler
Mandeep Gill
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