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  1. Stackups
  2. DevOps
  3. Code Coverage
  4. Code Coverage
  5. Codacy vs Coveralls

Codacy vs Coveralls

OverviewDecisionsComparisonAlternatives

Overview

Coveralls
Coveralls
Stacks1.7K
Followers278
Votes68
Codacy
Codacy
Stacks313
Followers551
Votes248

Codacy vs Coveralls: What are the differences?

What is Codacy? Automated Code Review. Codacy is an automated code review tool for Scala, Java, Ruby, JavaScript, PHP, Python, CoffeeScript and CSS. It's continuous static analysis without the hassle. Save time in Code Reviews. Tackle your technical debt.

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

Codacy can be classified as a tool in the "Code Review" category, while Coveralls is grouped under "Code Coverage".

Some of the features offered by Codacy are:

  • Monitoring of Technical Debt
  • Automated Code Review
  • New and Fixed Issues per commit

On the other hand, Coveralls provides the following key features:

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

"Automated code review" is the top reason why over 32 developers like Codacy, while over 44 developers mention "Free for public repositories" as the leading cause for choosing Coveralls.

According to the StackShare community, Coveralls has a broader approval, being mentioned in 58 company stacks & 45 developers stacks; compared to Codacy, which is listed in 44 company stacks and 23 developer stacks.

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Advice on Coveralls, Codacy

Felipe
Felipe

May 24, 2020

Needs advice

My website is brand new and one of the few requirements of testings I had to implement was code coverage. Never though it was so hard to implement using a #docker container.
Given my lack of experience, every attempt I tried on making a simple code coverage test using the 4 combinations of #TravisCI, #CircleCi with #Coveralls, #Codecov I failed. The main problem was I was generating the .coverage file within the docker container and couldn't access it with #TravisCi or #CircleCi, every attempt to solve this problem seems to be very hacky and this was not the kind of complexity I want to introduce to my newborn website.
This problem was solved using a specific action for #GitHubActions, it was a 3 line solution I had to put in my github workflow file and I was able to access the .coverage file from my docker container and get the coverage report with #Codecov.

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Comments

Detailed Comparison

Coveralls
Coveralls
Codacy
Codacy

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.

Codacy automates code reviews and monitors code quality on every commit and pull request on more than 40 programming languages reporting back the impact of every commit or PR, issues concerning code style, best practices and security.

Repository Coverage Statistics;Individual File Coverage Reports;Line By Line Coverage;Repository Overview
Available for cloud and self-hosted repositories;Static code analysis for +40 languages;Analysis for cloud infrastructure-as-code frameworks;Automatic analysis integrated in your CI;Code coverage tracking;Support for linter configuration files;1-click autofixes for GitHub;Static IP addresses for allowlisting Codacy;
Statistics
Stacks
1.7K
Stacks
313
Followers
278
Followers
551
Votes
68
Votes
248
Pros & Cons
Pros
  • 45
    Free for public repositories
  • 13
    Code coverage
  • 7
    Ease of integration
  • 2
    More stable than Codecov
  • 1
    Combines coverage from multiple/parallel test runs
Pros
  • 45
    Automated code review
  • 35
    Easy setup
  • 29
    Free for open source
  • 20
    Customizable
  • 18
    Helps reduce technical debt
Cons
  • 6
    No support for private Git or Azure DevOps git
Integrations
Travis CI
Travis CI
CircleCI
CircleCI
Semaphore
Semaphore
Jenkins
Jenkins
Codeship
Codeship
GitHub
GitHub
GitLab
GitLab
Slack
Slack
Bitbucket
Bitbucket
Jira
Jira

What are some alternatives to Coveralls, Codacy?

Code Climate

Code Climate

After each Git push, Code Climate analyzes your code for complexity, duplication, and common smells to determine changes in quality and surface technical debt hotspots.

Phabricator

Phabricator

Phabricator is a collection of open source web applications that help software companies build better software.

Codecov

Codecov

Our patrons rave about our elegant coverage reports, integrated pull request comments, interactive commit graphs, our Chrome plugin and security.

PullReview

PullReview

PullReview helps Ruby and Rails developers to develop new features cleanly, on-time, and with confidence by automatically reviewing their code.

Gerrit Code Review

Gerrit Code Review

Gerrit is a self-hosted pre-commit code review tool. It serves as a Git hosting server with option to comment incoming changes. It is highly configurable and extensible with default guarding policies, webhooks, project access control and more.

SonarQube

SonarQube

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.

RuboCop

RuboCop

RuboCop is a Ruby static code analyzer. Out of the box it will enforce many of the guidelines outlined in the community Ruby Style Guide.

CodeFactor.io

CodeFactor.io

CodeFactor.io automatically and continuously tracks code quality with every GitHub or BitBucket commit and pull request, helping software developers save time in code reviews and efficiently tackle technical debt.

ESLint

ESLint

A pluggable and configurable linter tool for identifying and reporting on patterns in JavaScript. Maintain your code quality with ease.

Amazon CodeGuru

Amazon CodeGuru

It is a machine learning service for automated code reviews and application performance recommendations. It helps you find the most expensive lines of code that hurt application performance and keep you up all night troubleshooting, then gives you specific recommendations to fix or improve your code.

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