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

Coveralls vs Coverity Scan

OverviewDecisionsComparisonAlternatives

Overview

Coveralls
Coveralls
Stacks1.7K
Followers278
Votes68
Coverity Scan
Coverity Scan
Stacks50
Followers185
Votes0

Coveralls vs Coverity Scan: What are the differences?

1. **Scalability**: Coveralls is more suitable for small to medium-sized projects, whereas Coverity Scan is designed for large-scale and enterprise-level projects with complex codebases. 2. **Integration with CI Tools**: Coveralls offers seamless integration with popular CI/CD tools like Travis CI, CircleCI, and Jenkins, while Coverity Scan has its own integrated workflow for analysis and reporting. 3. **Focused on Code Coverage**: Coveralls mainly focuses on code coverage metrics, providing insights into which parts of the code are being tested, while Coverity Scan focuses more on static analysis to detect potential security vulnerabilities and defects in the code. 4. **Pricing Model**: Coveralls typically offers a freemium model with pricing based on the number of users or repositories, whereas Coverity Scan is generally a subscription-based service with pricing determined by the level of support and features required. 5. **Ease of Use**: Coveralls is known for its user-friendly interface and easy setup process, making it accessible to developers of all skill levels, whereas Coverity Scan may have a steeper learning curve due to its advanced functionality and configuration options. 6. **Language Support**: Coveralls typically supports a wide range of programming languages such as Ruby, Python, Java, and JavaScript, while Coverity Scan focuses more on C, C++, and Java codebases.

In Summary, Coveralls and Coverity Scan differ in terms of scalability, integration with CI tools, focus on code coverage, pricing model, ease of use, and language support.

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Advice on Coveralls, Coverity Scan

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
Coverity Scan
Coverity Scan

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.

Coverity's implementation of static analysis can follow all the possible paths of execution through source code (including interprocedurally) and find defects and vulnerabilities caused by the conjunction of statements that are not errors independent of each other.

Repository Coverage Statistics;Individual File Coverage Reports;Line By Line Coverage;Repository Overview
Test every line of code and potential execution path.;The root cause of each defect is clearly explained, making it easy to fix bugs;Integrates with GitHub and Travis CI
Statistics
Stacks
1.7K
Stacks
50
Followers
278
Followers
185
Votes
68
Votes
0
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
No community feedback yet
Integrations
Travis CI
Travis CI
CircleCI
CircleCI
Semaphore
Semaphore
Jenkins
Jenkins
Codeship
Codeship
GitHub
GitHub
Travis CI
Travis CI

What are some alternatives to Coveralls, Coverity Scan?

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.

Codacy

Codacy

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.

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.

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