Best Free AI Code Refactoring Tools of 2025 - Page 2

Refraction serves as a powerful code-generation tool tailored for developers, employing AI to assist in writing code. This innovative platform enables users to produce unit tests, documentation, refactor existing code, and much more. It supports code generation in 34 programming languages, including Assembly, C#, C++, CoffeeScript, CSS, Dart, Elixir, Erlang, Go, GraphQL, Groovy, Haskell, HTML, Java, JavaScript, Kotlin, LaTeX, Less, Lua, MatLab, Objective-C, OCaml, Perl, PHP, Python, R Lang, Ruby, Rust, Sass/SCSS, Scala, Shell, SQL, Swift, and TypeScript. With Refraction, thousands of developers globally are streamlining their workflows, utilizing AI to automate tasks such as documentation creation, unit testing, and code refactoring. This tool not only enhances efficiency but also allows programmers to concentrate on more critical aspects of software development. By leveraging AI, you can refactor, optimize, fix, and style-check your code effortlessly. Additionally, it facilitates the generation of unit tests compatible with various testing frameworks and helps clarify the intent of your code, making it more accessible for others. Embrace the capabilities of Refraction and transform your coding experience today.

Refact.ai is an advanced AI-powered assistant that integrates directly into your IDE, offering intelligent code completion, real-time code suggestions, and automatic refactoring to streamline the coding process. By using the AI model trained on your codebase, Refact.ai adapts to your team's style, providing highly relevant recommendations to enhance productivity. Developers can also fine-tune the assistant to better suit their unique requirements, making it a powerful tool for personalized coding assistance. With support for all major IDEs and secure on-premise deployment, Refact.ai empowers developers to increase code quality, reduce time spent on manual tasks, and achieve faster results.

Tabby is a self-hosted, open-source AI coding assistant that aims to improve your development workflow by offering intelligent code completion, real-time suggestions, and smooth integration with your preferred integrated development environment (IDE). You can deploy Tabby on your own servers, which gives you the advantage of security and control over your codebase. It is compatible with major coding large language models (LLMs) such as CodeLlama, StarCoder, and CodeGen, allowing it to adapt to your unique coding style while delivering precise and context-sensitive support. Whether you are coding solo or collaborating in a team setting, Tabby not only streamlines your coding tasks but also minimizes errors and speeds up project timelines. With its user-friendly features and customizable options, Tabby stands out as an essential tool for developers looking to optimize their coding experience.

Experience a privacy-centric approach to pull request evaluations that offers detailed code recommendations on each line and an evolving interactive chat feature. The changes within the pull request are summarized effectively, making it easier to grasp the purpose behind the modifications. Automated release notes are generated, ensuring they can be seamlessly integrated into your release documentation. Each code alteration is scrutinized with a thorough analysis, providing clear and actionable feedback that's ready for implementation. You can engage with the bot by asking questions directly within your code and supplying additional context for it to generate code snippets. As your conversations with the bot increase, its intelligence grows, leading to quicker review cycles and high-caliber suggestions for code changes. Your information remains private, allowing it to tailor the review process to your needs. This system continually adapts based on your interactions, enhancing the relevance of its recommendations to match your coding style and preferences over time.

Fine is an innovative platform driven by artificial intelligence, aimed at supporting startups by automating various tasks in the software development lifecycle. This platform provides a variety of AI agent workflows that facilitate coding, debugging, testing, and code review, enabling teams to release daily updates and expedite the resolution of pull requests. Fine has the capability to independently generate and apply code, perform pull request assessments, create tests, and manage typical challenges without the need for constant oversight from human developers. It integrates smoothly with GitHub and is designed to accommodate asynchronous collaboration, making it an ideal choice for dynamic startup environments. Additionally, Fine offers real-time feedback and live previews, which not only enhance productivity but also optimize the overall development workflow. By leveraging such advanced features, teams can focus more on strategic tasks while the platform handles routine operations efficiently.

We are excited to unveil Codestral, our inaugural code generation model. This open-weight generative AI system is specifically crafted for tasks related to code generation, enabling developers to seamlessly write and engage with code via a unified instruction and completion API endpoint. As it becomes proficient in both programming languages and English, Codestral is poised to facilitate the creation of sophisticated AI applications tailored for software developers. With a training foundation that encompasses a wide array of over 80 programming languages—ranging from widely-used options like Python, Java, C, C++, JavaScript, and Bash to more niche languages such as Swift and Fortran—Codestral ensures a versatile support system for developers tackling various coding challenges and projects. Its extensive language capabilities empower developers to confidently navigate different coding environments, making Codestral an invaluable asset in the programming landscape.

Introducing MarsCode: an advanced AI development tool designed for immediate use. This innovative platform features an 'out-of-the-box cloud AI IDE' and a 'robust AI assistant,' making it an essential resource for developers seeking to enhance their learning and streamline their workflow. Among its standout features are: 1. A cloud-based AI IDE that frees developers from the limitations of specific devices and locations. 2. Integration options for local IDEs, which infuse traditional development practices with cutting-edge AI capabilities. 3. A suite of tools for code completion, bug fixing, and optimization, offering intelligent support throughout the entire coding journey. 4. An intelligent Q&A feature at the repository level, enabling developers to concentrate on their tasks with greater ease. 5. Versatile deployment support for various types of applications, including websites, AI plugins, and APIs, catering to a broad range of development needs. With MarsCode, developers not only gain access to powerful tools but also experience a newfound level of productivity and efficiency in their projects.

CodeQwen serves as the coding counterpart to Qwen, which is a series of large language models created by the Qwen team at Alibaba Cloud. Built on a transformer architecture that functions solely as a decoder, this model has undergone extensive pre-training using a vast dataset of code. It showcases robust code generation abilities and demonstrates impressive results across various benchmarking tests. With the capacity to comprehend and generate long contexts of up to 64,000 tokens, CodeQwen accommodates 92 programming languages and excels in tasks such as text-to-SQL queries and debugging. Engaging with CodeQwen is straightforward—you can initiate a conversation with just a few lines of code utilizing transformers. The foundation of this interaction relies on constructing the tokenizer and model using pre-existing methods, employing the generate function to facilitate dialogue guided by the chat template provided by the tokenizer. In alignment with our established practices, we implement the ChatML template tailored for chat models. This model adeptly completes code snippets based on the prompts it receives, delivering responses without the need for any further formatting adjustments, thereby enhancing the user experience. The seamless integration of these elements underscores the efficiency and versatility of CodeQwen in handling diverse coding tasks.

DeepCode AI serves as the foundation of Snyk code, making it the quickest and most precise Static Application Security Testing (SAST) solution available. By harnessing DeepCode AI within the Snyk platform, which leverages various AI models and is honed using data focused on security, Snyk provides users with the advantages of artificial intelligence while mitigating potential downsides. Supporting 11 programming languages, DeepCode AI is crafted to identify and remediate vulnerabilities, as well as address technical debt effectively. This innovative AI also facilitates Snyk's one-click security solutions and extensive application coverage, empowering developers to build swiftly while maintaining robust security measures. Developed and continuously improved by expert researchers, DeepCode AI relies on millions of open-source projects for its training, ensuring no customer data is utilized. Ultimately, DeepCode AI employs a hybrid strategy with multiple models and specialized training sets, all aimed at enhancing application security. This commitment to innovation ensures that developers can confidently deploy applications without compromising safety.

Introducing an advanced generative AI assistant designed specifically for software development tasks. Amazon Q agents enhance efficiency throughout the entire software development lifecycle by autonomously managing a variety of responsibilities, from feature implementation, documentation, testing, and code review to refactoring and executing software upgrades. With Amazon Q Developer, the entire development process is simplified. This expert tool is well-versed in AWS, providing support for optimizing cloud expenses and resources, offering advice on architectural best practices, investigating operational issues, and addressing networking problems. Additionally, Amazon Q Developer agents significantly expedite the transformation of large-scale enterprise workloads, including tasks such as transitioning .NET applications from Windows to Linux, modernizing mainframe applications, migrating VMware workloads, and upgrading Java. By streamlining these processes, Amazon Q Developer ultimately helps organizations reduce costs and improve overall productivity.

An autonomous coding assistant integrated directly within your IDE, this tool can create and modify files, execute commands, browse the web, and more, all with your explicit consent throughout the process. Cline is designed to tackle intricate software development challenges methodically. Equipped with capabilities to generate and adjust files, navigate extensive projects, utilize web resources, and perform terminal commands (once you authorize), he offers support that transcends mere code completion or technical assistance. Unlike traditional AI scripts that operate in isolated environments, this extension features a user-friendly interface that requires your approval for every file modification and command execution, ensuring a secure and user-friendly approach to harnessing the capabilities of autonomous AI. By incorporating such a system, developers can explore innovative solutions while maintaining control over their coding environment.

Aide takes the initiative to suggest solutions or request any potentially omitted files within the context. Our agent accomplishes this by addressing linter errors and integrating pertinent context via LSP tools. Feel free to apply AI-driven modifications throughout your coding experience. We maintain lightweight, VS Code-integrated checkpoints (we do not utilize git) to enable effortless restoration to earlier versions if the agent happens to err. Our goal is to make Aide resemble a true engineer, facilitating a collaborative programming experience. Engage in discussions about an issue by tagging the relevant file(s) and then proceed with edits, or start with a limited number of changes and explore their implications. Inspired by MacOS's spotlight feature, we've developed a floating widget that can be activated with CMD + K, allowing you to swiftly request alterations based on any active text selection. Additionally, we provide a utility named Sidecar, which manages the preparation and transmission of prompts to LLMs while granting them access to various editor functionalities, enriching the overall coding process. This innovative approach helps bridge the gap between human intuition and machine efficiency.

FauxPilot serves as an open-source, self-hosted substitute for GitHub Copilot, leveraging the SalesForce CodeGen models. It operates on NVIDIA's Triton Inference Server, utilizing the FasterTransformer backend to facilitate local code generation. The installation process necessitates Docker and an NVIDIA GPU with adequate VRAM, along with the capability to distribute the model across multiple GPUs if required. Users must download models from Hugging Face and perform conversions to ensure compatibility with FasterTransformer. This alternative not only provides flexibility for developers but also promotes an independent coding environment.

Trae is an innovative AI-driven integrated development environment (IDE) that aims to transform the developer experience by promoting effortless collaboration between humans and artificial intelligence. This collaborative approach guarantees that every task is managed by the most appropriate entity, optimizing both productivity and efficiency. By harmonizing human insight with the strengths of AI, Trae empowers developers to bring their products to market more swiftly and successfully. In addition, this synergy fosters an environment where creativity and technical prowess can flourish together.

The SWE-agent is a sophisticated AI-driven platform that automates a variety of tasks, including addressing GitHub issues, conducting cybersecurity operations such as Capture The Flag (CTF) challenges, and tackling coding problems. Utilizing advanced language models like GPT-4 or Claude, it operates within isolated computing environments to perform tasks independently, delivering customizable solutions tailored for developers and cybersecurity experts. This versatile tool caters to numerous applications, ranging from enhancing software repositories to detecting vulnerabilities and executing specialized tasks. Crafted by a collaboration of researchers from Princeton and Stanford University, SWE-agent exemplifies the integration of machine learning with effective problem-solving in the realms of software development and cybersecurity. With its innovative features, it represents a significant advancement in automating complex workflows for professionals in these fields.

Fynix serves as an AI-driven platform aimed at enhancing software development efficiency by providing smart coding assistance and agent-based code reviews. This tool seamlessly integrates with widely used IDEs such as VS Code, offering features like context-aware autocomplete, natural language inputs for code corrections and translations, along with automatic visualizations of code flow. The Code Assistant feature of Fynix enables developers to produce cleaner and more efficient code at an accelerated pace, and the forthcoming Code Quality Agent promises to streamline bug detection while upholding coding standards. Supporting a variety of programming languages and frameworks, and compatible with tools like Jira, Fynix proves to be a flexible solution for fostering improved coding practices and team collaboration. As developers strive for excellence in their coding endeavors, Fynix stands out as an essential ally in the software development landscape.

Solver represents a groundbreaking advancement in elastic engineering APIs, purposefully created to fully automate a wide range of programming responsibilities. This innovative tool allows software developers to delegate repetitive and laborious coding tasks, thus enabling them to devote more time to the imaginative aspects of their projects. Solver autonomously manages complex, multi-step processes, continuously enhancing its capabilities by interpreting external documentation and adjusting to the requirements of each project. It integrates effortlessly with existing integrated development environments through a cloud-based API, which means there’s no need to adopt a new system. By utilizing repository-based reasoning, it allows cutting-edge generative AI to interact directly with Git repositories, streamlining workflow efficiencies. Originating from the talented team that developed Siri and Viv, Solver upholds rigorous engineering standards, expanding the potential of AI in the realm of software development. Its scalability allows it to refine its operations as it progresses, and it is capable of executing tasks such as detecting security vulnerabilities and improving code, all while delivering results at a speed that often surpasses that of human teams. In essence, Solver not only enhances productivity but also reshapes the future landscape of coding practices.

Visual Studio IntelliCode enhances the development experience through AI-driven assistance. By prioritizing suggestions that you are most likely to need, IntelliCode helps streamline your workflow significantly. Its recommendations are informed by a wealth of information derived from numerous open-source projects on GitHub, each boasting over 100 stars. When used alongside the context of your existing code, the completion suggestions are customized to align with established coding practices. Beyond just completing statements, IntelliCode also offers signature assistance, suggesting the most relevant overload options based on the current context. Not only does IntelliCode provide personalized recommendations for your code, but it also facilitates sharing these insights across your team effortlessly. Thanks to this preview feature, you can create a team model that offers tailored suggestions for code outside the open-source realm, including methods from your custom utility classes or specialized libraries. Furthermore, by integrating our build task into your development pipeline, you can ensure that team completions remain current with any changes in the repository, fostering a more collaborative coding environment. This powerful tool ultimately empowers developers to work more efficiently and effectively within their teams.

We develop a streamlined version of your codebase, enabling AI to comprehend and collaborate on your coding tasks. Convert your codebase into actionable insights that are tailored for AI interpretation, leading to enhanced and precise coding recommendations. Unlock boundless possibilities; if you can envision it, you can now bring it to life. Produce complete, operational code that seamlessly integrates with your current project framework. Additionally, this innovative approach allows for greater efficiency and creativity in your coding endeavors.

Streamline your development process by automating the generation of pull request summaries. When you open a pull request, you'll receive a concise overview of the changes in mere seconds. This feature allows for quick comprehension of the impact of minor pull requests while also providing a significant advantage when dealing with larger ones. The process of code review often consumes a lot of time due to the necessary dialogue between the reviewer and the author, frequently over trivial changes that could be automated instead. By commenting on specific lines of code with the command /wtd and outlining your desired modifications, What The Diff will propose those adjustments directly within the pull request, enabling you to accept them effortlessly with a single click. Additionally, What The Diff evaluates the modifications in your pull requests and presents a summary in straightforward language, eliminating the need for manual summaries. With extensive training on a vast array of code data, it supports nearly all programming languages. You can easily install the GitHub app for free and test it out on any of your repositories, making it a valuable tool for enhancing team collaboration. Embrace this technology to significantly reduce the workload associated with code reviews.

Code Llama is an advanced language model designed to generate code through text prompts, distinguishing itself as a leading tool among publicly accessible models for coding tasks. This innovative model not only streamlines workflows for existing developers but also aids beginners in overcoming challenges associated with learning to code. Its versatility positions Code Llama as both a valuable productivity enhancer and an educational resource, assisting programmers in creating more robust and well-documented software solutions. Additionally, users can generate both code and natural language explanations by providing either type of prompt, making it an adaptable tool for various programming needs. Available for free for both research and commercial applications, Code Llama is built upon Llama 2 architecture and comes in three distinct versions: the foundational Code Llama model, Code Llama - Python which is tailored specifically for Python programming, and Code Llama - Instruct, optimized for comprehending and executing natural language directives effectively.

The leading open-source AI assistant. You can create custom autocomplete experiences and chats by connecting any models to any context. Remove the barriers that hinder productivity when developing software to remain in flow. Accelerate your development with a plug and play system that is easy to use and integrates into your entire stack. Set up your code assistant so that it can evolve with new capabilities. Continue autocompletes entire sections of code or single lines in any programming languages as you type. Ask questions about files, functions, the entire codebase and more by attaching code or context. Highlight code sections, then press the keyboard shortcut to convert code into natural language.

Codoki is an AI-powered engineering assistant that helps teams fix bugs, refactor code, and reduce tech debt—up to 50x faster. Unlike AI code assistants that just suggest snippets, Codoki integrates with your workflow, detects issues, automates fixes, and even acts as a 24/7 AI on-call engineer—reducing downtime and saving developer time. Engineering teams using Codoki ship faster, cut operational costs, and spend more time building instead of fixing.