Best AI Code Review Tools for Bitbucket

Cody is a coding assistant AI that lives inside your editor. It can find, explain and write code. Cody combines Large Language Models (LLMs), Sourcegraph Search, and Sourcegraph Code Intelligence to provide answers and eliminate toil for human programmers. Cody is your programmer friend who has read all the open source code, all the StackOverflow questions, and all the private code of your organization. He will always be there to answer any questions or suggest solutions based on his prior knowledge. Enterprises love Cody because it provides choice for: Any scale - Cody works for developer teams of any size, from startups to the biggest companies in the world. Any code host - Every code host and repository, to give the most accurate context from the largest codebases. Any LLM - Sourcegraph’s interoperability allows Cody to work with what LLM and context sources are best for your organization.

Amazon CodeGuru is an intelligent developer tool that uses machine learning to make intelligent recommendations for improving code quality, and identifying the most costly lines of code in an application. Integrate Amazon CodeGuru in your existing software development workflow to get built-in code reviews that will help you identify and optimize the most expensive lines of code to lower costs. Amazon CodeGuru Profiler allows developers to find the most expensive lines in an application's code. It also provides visualizations and suggestions on how to improve code to make it more affordable. Amazon CodeGuru Reviewer uses machine-learning to identify critical issues and difficult-to-find bugs in application development to improve code quality.

Qodo, formerly Codium, analyzes your code to find bugs before you release. Qodo maps the behaviors of your code, identifies edge cases and tags anything suspicious. It then generates meaningful and clear unit tests that match the behavior of your code. You can see how your code behaves and how changes to your code affect the rest of the code. Code coverage is broken. Meaningful tests check functionality and give you the confidence to commit. Spend less time writing questionable tests and more time developing features that are useful to your users. Qodo analyzes your code, docstring and comments to suggest tests as you type. You only need to add them to your suite. Qodo focuses on code integrity. It generates tests that help you understand your code, find edge cases and suspicious behavior; and make your code more robust.

Snyk is the leader in developer security. We empower the world’s developers to build secure applications and equip security teams to meet the demands of the digital world. Our developer-first approach ensures organizations can secure all of the critical components of their applications from code to cloud, leading to increased developer productivity, revenue growth, customer satisfaction, cost savings and an overall improved security posture. Snyk is a developer security platform that automatically integrates with a developer’s workflow and is purpose-built for security teams to collaborate with their development teams.

CodeScene's powerful features go beyond traditional code analysis. Visualize and evaluate all the factors that influence software delivery and quality, not just the code itself. Make informed, data-driven decisions based on CodeScene’s actionable insights and recommendations. CodeScene guides developers and technical leaders to: - Get a holistic overview and evolution of your software system in one single dashboard. - Identify, prioritize, and tackle technical debt based on return on investment. - Maintain a healthy codebase with powerful CodeHealth™ Metrics, spend less time on rework and more time on innovation. - Seamlessly integrate with Pull Requests and editors, get actionable code reviews and refactoring recommendations. - Set Improvement goals and quality gates for teams to work towards while monitoring the progress. - Support retrospectives by identifying areas for improvement. - Benchmark performance against personalized trends. - Understand the social side of the code, measure socio-technical factors like key personnel dependencies, knowledge sharing and inter-team coordination.

Never let onboarding, knowledge silos or context switching slow down your progress. Swimm allows you to create and edit documents that are linked with your code, autosynced, integrated into your workflow, and automatically edited by Swimm. Swimm's language-agnostic editor is paired with Smart Tokens, Snippet Studio, and is the foundation of modern documentation. Create media-rich documents that are compatible with the code. Swimm's Autosync algorithm helps keep your documentation in sync by refactoring and organizing. You don't need to worry about file names, function names or implementation changes. Swimm will keep up with your code. Swimm will monitor your documentation as your code changes and notify you if any of your changes have an impact on your documentation. You can access docs right next the code they reference. Keep your IDE open and continue your work flow. Clicking on a link will open your IDE in a new tab. This tab will contain the Markdown documentation.

Codacy is an automated code review tool. It helps identify problems through static code analysis. This allows engineering teams to save time and tackle technical debt. Codacy seamlessly integrates with your existing workflows on Git provider as well as with Slack and JIRA or using Webhooks. Each commit and pull-request includes notifications about security issues, code coverage, duplicate code, and code complexity. Advanced code metrics provide insight into the health of a project as well as team performance and other metrics. The Codacy CLI allows you to run Codacy code analysis locally. This allows teams to see Codacy results without needing to check their Git provider, or the Codacy app. Codacy supports more than 30 programming languages and is available in free open source and enterprise versions (cloud or self-hosted). For more see https://www.codacy.com/

Get code reviews on-demand from experts, vetted by AI. Every time you open a Pull Request, senior engineers will be added to your team. AI-assisted code review will help you deliver better, more secure software faster. PullRequest can adapt to the needs of any development team, whether it's 5 or 5,000. Our reviewers help your team find security vulnerabilities, hidden bugs, and fix any performance issues before they are released. All of this can be done using your existing tools. AI analysis enhances the expertise of human reviewers to identify high-risk security areas. Intelligent static analysis using open source tools combined with proprietary AI. Shown to reviewers for greater insights. Save your senior staff time. While other members of your group are busy building, you can make meaningful progress in resolving problems and improving code.

Summary pull request changes in a concise manner to help the team understand their impact. Code quality issues and antipatterns are detected and automatically fixed for 30+ languages. Scan each code change to detect OWASP, NIST, SANS and CWE vulnerabilities and fix them. Scan each PR against more than 10,000 policies to detect and understand infrastructure as code issues. Protects sensitive data in your codebase including API keys, tokens and other secrets. Identify and understand the impact of potential issues in data structures and code logic. Get instant visibility into the health of your code and infrastructure with a Code Health dashboard. Identify issues of high severity, understand their impact and fix them. Receive weekly executive reports about new issues, fixes, and resolutions pending. Your pair programmer will help you to find and automatically fix over 5000+ security vulnerabilities and code quality issues without leaving your IDE.

Metabob detects coding errors created by humans or AI, explains them, and fixes them. Metabob uses proprietary graph neural network to detect problems, and LLMs explain and resolve them. This combines the best of both worlds. GNN detects problematic code and classifies it with contextual understanding. Metabob's backend stores problematic code and context enriched with context. The backend stores the information and passes it to an integrated LLM. The LLM provides context-sensitive explanations and solutions to problems. Metabob's AI has been trained by millions of bug fixes made by experienced developers. Metabob's ability to understand context and code logic allows it to detect complex issues that span multiple codebases, and automatically generate solutions. Metabob's AI code reviews detect hundreds of logical issues, ranging from race conditions to unhandled edges cases. These problems are not detectable by static analysis tools.