What is Codecov and what are its top alternatives?
Top Alternatives to Codecov
- 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. ...
- 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. ...
- 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. ...
- 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. ...
- JaCoCo
It is a free code coverage library for Java, which has been created based on the lessons learned from using and integration existing libraries for many years. ...
- Istanbul
It is a JS code coverage tool that computes statement, line, function and branch coverage with module loader hooks to transparently add coverage when running tests. Supports all JS coverage use cases including unit tests, server side functional tests and browser tests. Built for scale. ...
- uberalls
Code coverage metric storage service. Provide coverage metrics on differentials with Phabricator and Jenkins, just like Coveralls does for GitHub and TravisCI. ...
Codecov alternatives & related posts
- Auto sync with Github71
- Simple grade system that motivates to keep code clean49
- Better coding45
- Free for open source30
- Hotspots for quick refactoring candidates21
- Continued encouragement to a have better / cleaner code15
- Great UI13
- Makes you a better coder11
- Duplication Detection10
- Safe and Secure5
- Extremely accurate in telling you the errors2
- GitHub only2
- Python inspection2
- Great open community2
- GitHub integration, status inline in PRs2
- Uses rubocop2
- Private2
- Locally Installable API1
- Learning curve, static analysis comparable to eslint2
- Complains about small stylistic decisions1
related Code Climate posts
The continuous integration process for our Rails backend app starts by opening a GitHub pull request. This triggers a CircleCI build and some Code Climate checks.
The CircleCI build is a workflow that runs the following jobs:
- check for security vulnerabilities with Brakeman
- check code quality with RuboCop
- run RSpec tests in parallel with the knapsack gem, and output test coverage reports with the simplecov gem
- upload test coverage to Code Climate
Code Climate checks the following:
- code quality metrics like code complexity
- test coverage minimum thresholds
The CircleCI jobs and Code Climate checks above have corresponding GitHub status checks.
Once all the mandatory GitHub checks pass and the code+functionality have been reviewed, developers can merge their pull request into our Git master
branch. Code is then ready to deploy!
#ContinuousIntegration
Coveralls
- Free for public repositories45
- Code coverage13
- Ease of integration7
- More stable than Codecov2
- Combines coverage from multiple/parallel test runs1
related Coveralls posts
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.
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.
- Tracks code complexity and smell trends26
- IDE Integration16
- Complete code Review9
- Difficult to deploy1
- Sales process is long and unfriendly7
- Paid support is poor, techs arrogant and unhelpful7
- Does not integrate with Snyk1
related SonarQube posts
Our whole DevOps stack consists of the following tools:
- GitHub (incl. GitHub Pages/Markdown for Documentation, GettingStarted and HowTo's) for collaborative review and code management tool
- Respectively Git as revision control system
- SourceTree as Git GUI
- Visual Studio Code as IDE
- CircleCI for continuous integration (automatize development process)
- Prettier / TSLint / ESLint as code linter
- SonarQube as quality gate
- Docker as container management (incl. Docker Compose for multi-container application management)
- VirtualBox for operating system simulation tests
- Kubernetes as cluster management for docker containers
- Heroku for deploying in test environments
- nginx as web server (preferably used as facade server in production environment)
- SSLMate (using OpenSSL) for certificate management
- Amazon EC2 (incl. Amazon S3) for deploying in stage (production-like) and production environments
- PostgreSQL as preferred database system
- Redis as preferred in-memory database/store (great for caching)
The main reason we have chosen Kubernetes over Docker Swarm is related to the following artifacts:
- Key features: Easy and flexible installation, Clear dashboard, Great scaling operations, Monitoring is an integral part, Great load balancing concepts, Monitors the condition and ensures compensation in the event of failure.
- Applications: An application can be deployed using a combination of pods, deployments, and services (or micro-services).
- Functionality: Kubernetes as a complex installation and setup process, but it not as limited as Docker Swarm.
- Monitoring: It supports multiple versions of logging and monitoring when the services are deployed within the cluster (Elasticsearch/Kibana (ELK), Heapster/Grafana, Sysdig cloud integration).
- Scalability: All-in-one framework for distributed systems.
- Other Benefits: Kubernetes is backed by the Cloud Native Computing Foundation (CNCF), huge community among container orchestration tools, it is an open source and modular tool that works with any OS.
I'm planning to create a web application and also a mobile application to provide a very good shopping experience to the end customers. Shortly, my application will be aggregate the product details from difference sources and giving a clear picture to the user that when and where to buy that product with best in Quality and cost.
I have planned to develop this in many milestones for adding N number of features and I have picked my first part to complete the core part (aggregate the product details from different sources).
As per my work experience and knowledge, I have chosen the followings stacks to this mission.
UI: I would like to develop this application using React, React Router and React Native since I'm a little bit familiar on this and also most importantly these will help on developing both web and mobile apps. In addition, I'm gonna use the stacks JavaScript, jQuery, jQuery UI, jQuery Mobile, Bootstrap wherever required.
Service: I have planned to use Java as the main business layer language as I have 7+ years of experience on this I believe I can do better work using Java than other languages. In addition, I'm thinking to use the stacks Node.js.
Database and ORM: I'm gonna pick MySQL as DB and Hibernate as ORM since I have a piece of good knowledge and also work experience on this combination.
Search Engine: I need to deal with a large amount of product data and it's in-detailed info to provide enough details to end user at the same time I need to focus on the performance area too. so I have decided to use Solr as a search engine for product search and suggestions. In addition, I'm thinking to replace Solr by Elasticsearch once explored/reviewed enough about Elasticsearch.
Host: As of now, my plan to complete the application with decent features first and deploy it in a free hosting environment like Docker and Heroku and then once it is stable then I have planned to use the AWS products Amazon S3, EC2, Amazon RDS and Amazon Route 53. I'm not sure about Microsoft Azure that what is the specialty in it than Heroku and Amazon EC2 Container Service. Anyhow, I will do explore these once again and pick the best suite one for my requirement once I reached this level.
Build and Repositories: I have decided to choose Apache Maven and Git as these are my favorites and also so popular on respectively build and repositories.
Additional Utilities :) - I would like to choose Codacy for code review as their Startup plan will be very helpful to this application. I'm already experienced with Google CheckStyle and SonarQube even I'm looking something on Codacy.
Happy Coding! Suggestions are welcome! :)
Thanks, Ganesa
- Automated code review44
- Easy setup35
- Free for open source29
- Customizable20
- Helps reduce technical debt18
- Better coding14
- Best scala support13
- Faster Employee Onboarding11
- Duplication detector10
- Great UI10
- PHP integration9
- Python inspection6
- Tools for JVM analysis5
- Many integrations5
- Github Integration4
- Must-have for Java3
- Easy Travis integration3
- Items can be ignored in the UI3
- Asdasdas3
- Gitlab2
- Asdas0
- No support for private Git or Azure DevOps git6
related Codacy posts
I'm planning to create a web application and also a mobile application to provide a very good shopping experience to the end customers. Shortly, my application will be aggregate the product details from difference sources and giving a clear picture to the user that when and where to buy that product with best in Quality and cost.
I have planned to develop this in many milestones for adding N number of features and I have picked my first part to complete the core part (aggregate the product details from different sources).
As per my work experience and knowledge, I have chosen the followings stacks to this mission.
UI: I would like to develop this application using React, React Router and React Native since I'm a little bit familiar on this and also most importantly these will help on developing both web and mobile apps. In addition, I'm gonna use the stacks JavaScript, jQuery, jQuery UI, jQuery Mobile, Bootstrap wherever required.
Service: I have planned to use Java as the main business layer language as I have 7+ years of experience on this I believe I can do better work using Java than other languages. In addition, I'm thinking to use the stacks Node.js.
Database and ORM: I'm gonna pick MySQL as DB and Hibernate as ORM since I have a piece of good knowledge and also work experience on this combination.
Search Engine: I need to deal with a large amount of product data and it's in-detailed info to provide enough details to end user at the same time I need to focus on the performance area too. so I have decided to use Solr as a search engine for product search and suggestions. In addition, I'm thinking to replace Solr by Elasticsearch once explored/reviewed enough about Elasticsearch.
Host: As of now, my plan to complete the application with decent features first and deploy it in a free hosting environment like Docker and Heroku and then once it is stable then I have planned to use the AWS products Amazon S3, EC2, Amazon RDS and Amazon Route 53. I'm not sure about Microsoft Azure that what is the specialty in it than Heroku and Amazon EC2 Container Service. Anyhow, I will do explore these once again and pick the best suite one for my requirement once I reached this level.
Build and Repositories: I have decided to choose Apache Maven and Git as these are my favorites and also so popular on respectively build and repositories.
Additional Utilities :) - I would like to choose Codacy for code review as their Startup plan will be very helpful to this application. I'm already experienced with Google CheckStyle and SonarQube even I'm looking something on Codacy.
Happy Coding! Suggestions are welcome! :)
Thanks, Ganesa
It is very important to have clean code. To be sure that the code quality is not really bad I use a few tools. I love SonarQube with many relevant hints and deep analysis of code. codebeat isn't so detailed, but it can find complexity issues and duplications. Codacy cannot find more bugs then your IDE. The winner for me is SonarQube that shows me really relevant bugs in my code.