Open Source Linux Code Review Software
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Code Review Software for Linux
View 11 business solutionsBrowse free open source Code Review software and projects for Linux below. Use the toggles on the left to filter open source Code Review software by OS, license, language, programming language, and project status.
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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tkdiff
Side-by-side diff viewer, editor and merge preparer
tkdiff is a graphical front end to the diff program. It provides a side-by-side view of the differences between two text files, along with several innovative features such as diff bookmarks, a graphical map of differences for quick navigation, and a facility for slicing diff regions to achieve exactly the merge output desired. -
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SonarQube
Continuous inspection
SonarQube empowers all developers to write cleaner and safer code. Thousands of automated Static Code Analysis rules, protecting your app on multiple fronts, and guiding your team. Catch tricky bugs to prevent undefined behavior from impacting end-users. Fix vulnerabilities that compromise your app, and learn AppSec along the way with Security Hotspots. Make sure your codebase is clean and maintainable, to increase developer velocity! We embrace progress - whether it's multi-language applications, teams composed of different backgrounds or a workflow that's a mix of modern and legacy, SonarQube has you covered. SonarQube fits with your existing tools and pro-actively raises a hand when the quality or security of your codebase is at risk. SonarQube can analyse branches of your repo, and notify you directly in your Pull Requests! -
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Eclipse Checkstyle Plug-in
Integrates Checkstye into the Eclipse IDE
The Eclipse Checkstyle plug-in integrates the Checkstyle Java code auditor into the Eclipse IDE. The plug-in provides real-time feedback to the user about violations of rules that check for coding style and possible error prone code constructs. -
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Pylint
It's not just a linter that annoys you!
Pylint is a static code analyzer for Python 2 or 3. The latest version supports Python 3.7.2 and above. Pylint analyses your code without actually running it. It checks for errors, enforces a coding standard, looks for code smells, and can make suggestions about how the code could be refactored. Projects that you might want to use alongside pylint include flake8 (faster and simpler checks with very few false positives), mypy, pyright or pyre (typing checks), bandit (security-oriented checks), black and isort (auto-formatting), autoflake (automated removal of unused import or variable), pyupgrade (automated upgrade to newer python syntax) and pydocstringformatter (automated pep257). Pylint isn't smarter than you: it may warn you about things that you have conscientiously done or checks for some things that you don't care about. During adoption, especially in a legacy project where pylint was never enforced. -
Gemini 3 and 200+ AI Models on One PlatformBuild generative AI apps with Vertex AI. Switch between models without switching platforms.
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Roslyn
The .NET Compiler Platform
Roslyn provides rich, code analysis APIs to open source C# and Visual Basic compilers. This enables you to access a wealth of information about your code from compilers, which you can then use for code-related tasks in your tools and applications. Roslyn dramatically lowers the barrier to entry for creating code-focused tools and applications, creating many opportunities for innovation. -
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Chroma
A general purpose syntax highlighter in pure Go
As Chroma has just been released, its API is still in flux. That said, the high-level interface should not change significantly. Chroma takes source code and other structured text and converts it into syntax-highlighted HTML, ANSI-coloured text, etc. Chroma is based heavily on Pygments and includes translators for Pygments lexers and styles. ABAP, ABNF, ActionScript, ActionScript 3, Ada, Angular2, ANTLR, ApacheConf, APL, AppleScript, Arduino, Awk. PacmanConf, Perl, PHP, PHTML, Pig, PkgConfig, PL/pgSQL, plaintext, Pony, PostgreSQL SQL dialect, PostScript, POVRay, PowerShell, Prolog, PromQL, Properties, Protocol Buffer, PSL, Puppet, Python 2, Python. Lexers convert source text into a stream of tokens, styles specify how token types are mapped to colours, and formatters convert tokens and styles into formatted output. A package exists for each of these, containing a global Registry variable with all of the registered implementations. -
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Sentry
Cross-platform application monitoring and error tracking software
Sentry is a cross-platform, self-hosted error monitoring solution that helps software teams discover, monitor and fix errors in real-time. The most users and logs will have to provide are the clues, and Sentry provides the answers. Sentry offers enhanced application performance monitoring through information-laden stack traces. It lets you build better software faster and more efficiently by showing you all issues in one place and providing the trail of events that lead to errors. It also provides real-time monitoring and data visualization through dashboards. Sentry’s server is in Python, but its API enables for sending events from any language, in any application. More than fifty-thousand companies already ship better software faster thanks to Sentry; let yours be one of them! -
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Flow
A static type checker for JavaScript
Flow is a static type checker for JavaScript. It was designed to help improve code quality and developer productivity. It does this through several smart capabilities. First, it identifies problems as you code, so you no longer have to waste time guessing and checking again and again. Second, it understands your code and makes its knowledge available, allowing you to build other smart tools on top of it. Third, it helps you refactor safely so you can focus on the changes you want to make and not on what you might break. Lastly, it can help prevent bad rebases and protect your carefully designed library, which is especially relevant when working with a large group of developers. Flow integrates with many tools, so you can easily and seamlessly insert it into your existing workflow and toolchain. -
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cargo-crev
A cryptographically verifiable code review system for the cargo
A cryptographically verifiable code review system for the cargo (Rust) package manager. cargo-crev is an implementation of Crev as a command-line tool integrated with cargo. This tool helps Rust users evaluate the quality and trustworthiness of their package dependencies. Crev is a language and ecosystem agnostic, distributed code review system. Use reviews produced by other users. Increase the trustworthiness of your own code. Build a web of trust of other reputable users to help verify the code you use. Static binaries are available from the releases page. Crev is a system for verifying the security and reliability of dependencies based on collaborative code reviews. Crev users review the source code of packages/libraries/crates and share their findings with others. Crev then uses Web of Trust to select trusted reviews and judge the reputation of projects' dependencies. -
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10
Static Analysis Tools for PHP
Docker image that provides static analysis tools for PHP
Docker image providing static analysis tools for PHP. The list of available tools and the installer is actually managed in the jakzal/toolbox repository. Docker image with quality analysis tools for PHP. To run the selected tool inside the container, you'll need to mount the project directory on the container with -v "$(pwd):/project". Some tools like to write to the /tmp directory (like PHPStan, or Behat in some cases), therefore it's often useful to share it between docker runs, i.e. with -v "$(pwd)/tmp-phpqa:/tmp". If you want to be able to interrupt the selected tool if it takes too much time to complete, you can use the --init option. Some tools are not included in the docker image, to use them refer to their documentation. Provides utilities to report legacy tests and usage of deprecated code. -
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RefactorFirst
Identifies and prioritizes God Classes Highly Coupled classes
A tool designed to automate code refactoring for developers, reducing technical debt and improving code quality. -
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nvim-regexplainer
Describe the regexp under the cursor
Describe the regular expression under the cursor. You need to install regex with nvim-treesitter, as well as the grammar for whichever host language you're using. -
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Codeball AI
AI Code Review that finds bugs and fast-tracks your code
Codeball is a code review AI that scores pull requests on a grade from 0 (needs careful review) to 1. Use Codeball to add labels to help you focus, auto-approve PRs, and more. The Codeball action is easy to use (sane defaults) and is highly customizable to fit your workflow when needed. Label PRs when you should review them with caution. Stay sharp, don't let the bugs pass through. Identifies and approves or labels safe PRs. Save time by fast-tracking PRs that are easy to review. Fully customizable and programmable with GitHub Actions. Codeball Actions are built on multiple smaller building blocks, that are heavily configurable through GitHub Actions. Codeball uses a deep learning model that has been trained on over 1 million Pull Requests. For each contribution, it considers hundreds of inputs. Codeball is optimized for precision, which means it only approves contributions that it's really confident in. -
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HTMLHint
The static code analysis tool you need for your HTML
Static code analysis tool you need for your HTML. By default, htmlhint looks for a .htmlhintrc file in the current directory and all parent directories and applies its rules when parsing a file. -
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Kodus
AI code reviews, just like your senior dev would do
Kodus-AI is a framework for building, training, and deploying intelligent agents and models, especially focusing on practical AI workflows for businesses and automation. It provides a structured set of tools and abstractions that help teams design agent behaviors, orchestrate data pipelines, optimize inference, and integrate AI capabilities with applications or services. The platform often includes model management, scalable training workflows, and orchestration patterns that help teams move from research or prototypes to production-ready AI deployments. Through configurable pipelines and a focus on modularity, it supports experimentation while maintaining reproducibility and performance. Its tooling is typically designed to handle real-world imperatives like logging, monitoring, versioning, and hooking into operational infrastructure. -
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SimpleCov
Code coverage for Ruby with a powerful configuration library
Code coverage for Ruby with a powerful configuration library and automatic merging of coverage across test suites. SimpleCov is a code coverage analysis tool for Ruby. It uses Ruby's built-in Coverage library to gather code coverage data, but makes processing its results much easier by providing a clean API to filter, group, merge, format, and display those results, giving you a complete code coverage suite that can be set up with just a couple lines of code. SimpleCov/Coverage track covered ruby code, gathering coverage for common templating solutions like erb, slim and haml is not supported. In most cases, you'll want overall coverage results for your projects, including all types of tests, Cucumber features, etc. SimpleCov automatically takes care of this by caching and merging results when generating reports, so your report actually includes coverage across your test suites and thereby gives you a better picture of blank spots. -
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diff-so-fancy
Make your diffs human readable instead of machine readable
diff-so-fancy strives to make your diffs human readable instead of machine readable. This helps improve code quality and helps you spot defects faster. diff-so-fancy is also available from NPM, Nix, brew, and as a package on Arch and Debian Linux. Windows users may need to install MinGW or the Windows subsystem for Linux. By default, the separator for the file header uses Unicode line-drawing characters. If this is causing output errors on your terminal, set this to false to use ASCII characters instead. By default, the separator for the file header spans the full width of the terminal. Use this setting to set the width of the file header manually. Pull requests are quite welcome, and should target the next branch. You can simplify git header chunks to a more human readable format. We are also looking for any feedback or ideas on how to make diff-so-fancy even fancier. -
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wemake-python-styleguide
The strictest and most opinionated python linter ever!
Welcome to the strictest and most opinionated Python linter ever. wemake-python-styleguide is actually a flake8 plugin with some other plugins as dependencies. Ensures consistency - no matter who works on it, the end product will always be the same dependable code. Helps avoid potential bugs - strict rules make sure that you don't make common mistakes. Efficient code reviews - each piece of code has a similar familiar style and syntax. If it passes all the checks, there's little left to review! Fewer code revisions - strict linting ensures that you don't have to re-write the codebase again and again. Reduce code redundancy - Sometimes we write complex code as we are thinking in a certain way about a problem. The linter offers suggestions that can help simplify the code and eliminate redundant statements. The ultimate goal of this project is to make all people write exactly the same Python code. -
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DeepCode for Visual Studio Code
DeepCode extension for Visual Studio Code
DeepCode AI has always been the backbone of Snyk code, which is why it's the fastest, most accurate SAST on the market. DeepCode AI, powering the Snyk platform, utilizes multiple AI models, is trained on security-specific data, and is all curated by top security researchers to give you all the power of AI without any of the drawbacks. With 11 supported languages, and multiple AI models, Snyk's DeepCode AI was designed to find and fix vulnerabilities and manage tech debt. DeepCode AI powers Snyk's one-click security fixes and comprehensive app coverage, letting developers build fast while staying secure. Our specialized DeepCode AI is built and refined by top-tier researchers that use training data from millions of open source projects, never customer data. DeepCode AI's hybrid approach uses multiple models and security-specific training sets for one purpose, to secure applications. -
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Highlight.js
JavaScript syntax highlighter with language auto-detection
Highlight.js is a syntax highlighter written in JavaScript. It works in the browser as well as on the server. It can work with pretty much any markup, doesn’t depend on any other frameworks, and has automatic language detection. Highlight.js supports over 180 languages in the core library. There are also 3rd party language definitions available to support even more languages. We strongly recommend <pre><code> wrapping for code blocks. It's quite semantic and "just works" out of the box with zero fiddling. It is possible to use other HTML elements (or combos), but you may need to pay special attention to preserving linebreaks. You can run highlighting inside a web worker to avoid freezing the browser window while dealing with very big chunks of code. -
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Matter AI
Matter AI is open-source AI Code Reviewer Agent
Matter AI is an AI-powered platform designed to enhance productivity through automated content generation, data analysis, and decision support. It leverages machine learning models to process text, analyze patterns, and generate insights, making it suitable for businesses looking to optimize data-driven decision-making. Matter AI integrates with various data sources and provides customizable AI workflows tailored to different industries. -
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Patchwork
Automate code reviews, patching and documentation
Patchwork automates development gruntwork like PR reviews, bug fixing, security patching, and more using a self-hosted CLI agent and your preferred LLMs. -
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PyTorch Lightning
The lightweight PyTorch wrapper for high-performance AI research
Scale your models, not your boilerplate with PyTorch Lightning! PyTorch Lightning is the ultimate PyTorch research framework that allows you to focus on the research while it takes care of everything else. It's designed to decouple the science from the engineering in your PyTorch code, simplifying complex network coding and giving you maximum flexibility. PyTorch Lightning can be used for just about any type of research, and was built for the fast inference needed in AI research and production. When you need to scale up things like BERT and self-supervised learning, Lightning responds accordingly by automatically exporting to ONNX or TorchScript. PyTorch Lightning can easily be applied for any use case. With just a quick refactor you can run your code on any hardware, run distributed training, perform logging, metrics, visualization and so much more! -
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Semantic
Parsing, analyzing, and comparing source code across many languages
semantic is a Haskell library and command line tool for parsing, analyzing, and comparing source code. Run semantic --help for complete list of up-to-date options. Semantic uses tree-sitter to generate parse trees, but layers in a more generalized notion of syntax terms across all supported programming languages. We'll see why this is important when we get to diffs and program analysis, but for now let's just inspect some output. It helps to have a simple program to parse. Symbols are named identifiers driven by the ASTs. This is the format that github.com uses to generate code navigation information allowing c-tags style lookup of symbolic names for fast, incremental navigation in all the supported languages. The incremental part is important because files change often so we want to be able to parse just what's changed and not have to analyze the entire project again. -
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Sourcery AI Code Review
Instant AI code reviews
Sourcery is an AI-powered code assistant designed to help developers write cleaner, more maintainable Python code by suggesting real-time refactorings, improvements, and best-practice rewrites directly in popular editors and IDEs. Instead of just offering autocomplete, Sourcery analyzes existing functions and code patterns to provide context-aware suggestions that can simplify logic, reduce duplication, improve naming, and correct anti-patterns, helping developers adhere to idiomatic style without manual review. It integrates directly into development workflows through plugins for editors like VS Code, JetBrains IDEs, and command-line tools, so suggestions appear where developers already write code. Because it continuously evaluates changes, it can catch inefficiencies and suggest enhancements both while typing and during dedicated refactor passes. Teams can standardize code quality across codebases by adopting Sourcery’s automated suggestions as part of review or CI pipelines.
