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Coveralls VS GitPrime

Compare Coveralls VS GitPrime and see what are their differences

Coveralls logo Coveralls

Coveralls is a code coverage history and tracking tool that tests coverage reports and statistics for engineering teams.

GitPrime logo GitPrime

GitPrime uses data from any Git based code repository to give management the software engineering metrics needed to move faster and optimize work patterns.
  • Coveralls Landing page
    Landing page //
    2023-01-24
  • GitPrime Landing page
    Landing page //
    2023-06-25

Coveralls videos

High Quality Mens Work Clothing Long Sleeve Coveralls review

More videos:

  • Review - Scentlok coveralls review!

GitPrime videos

Enabling High Performance teams with GitPrime

Category Popularity

0-100% (relative to Coveralls and GitPrime)
Code Coverage
64 64%
36% 36
Data Dashboard
0 0%
100% 100
Code Analysis
100 100%
0% 0
Predictive Analytics
0 0%
100% 100

User comments

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Social recommendations and mentions

Based on our record, Coveralls seems to be more popular. It has been mentiond 13 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Coveralls mentions (13)

  • GitHub Actions for Perl Development
    Cpan_coverage: This calculates the coverage of your test suite and reports the results. It also uploads the results to coveralls.io. - Source: dev.to / 5 months ago
  • Perl Testing in 2023
    I will normally use GitHub Actions to automatically run my test suite on each push, on every major version of Perl I support. One of the test runs will load Devel::Cover and use it to upload test coverage data to Codecov and Coveralls. - Source: dev.to / over 1 year ago
  • free-for.dev
    Coveralls.io — Display test coverage reports, free for Open Source. - Source: dev.to / over 1 year ago
  • Containers for Coverage
    Several years ago I got into Travis CI and set up lots of my GitHub repos so they automatically ran the tests each time I committed to the repo. Later on, I also worked out how to tie those test runs into Coveralls.io so I got pretty graphs of how my test coverage was looking. I gave a talk about what I had done. - Source: dev.to / over 1 year ago
  • Comprehensive coverage Jest+Playwright in Next.js TS
    This approach will create two json coverage files, which will be merged together by NYC. Therefore the results will be purely local. If You don't mind using online tools like Codecov or Coveralls for merging data from different tests, then go ahead and use them. They will probably also be more accurate. But if You still want to learn how to get coverage from E2E, then please read through. - Source: dev.to / almost 2 years ago
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GitPrime mentions (0)

We have not tracked any mentions of GitPrime yet. Tracking of GitPrime recommendations started around Mar 2021.

What are some alternatives?

When comparing Coveralls and GitPrime, you can also consider the following products

CodeClimate - Code Climate provides automated code review for your apps, letting you fix quality and security issues before they hit production. We check every commit, branch and pull request for changes in quality and potential vulnerabilities.

Waydev - Waydev analyzes your codebase from Github, Gitlab, Azure DevOps & Bitbucket to help you bring out the best in your engineers work.

Codacy - Automatically reviews code style, security, duplication, complexity, and coverage on every change while tracking code quality throughout your sprints.

LinearB - LinearB delivers software leaders the insights they need to make their engineering teams better through a real-time SaaS platform. Visibility into key metrics paired with automated improvement actions enables software leaders to deliver more.

SonarQube - SonarQube, a core component of the Sonar solution, is an open source, self-managed tool that systematically helps developers and organizations deliver Clean Code.

Haystack Analytics - Ship faster and improve team satisfaction with engineering analytics powered by your Github data.