List of the Top AI Code Refactoring Tools for Mac in 2025 - Page 2

Safurai is an AI-driven IDE extension designed to assist developers by enhancing the speed of coding, debugging, documentation, and various other tasks. It functions as a virtual assistant, offering solutions and suggestions for any challenges encountered throughout the software development process. By using Safurai, developers can elevate their workflow and enhance the quality of their code, ultimately leading to a more efficient development experience. Comprising a collection of non-proprietary Large Language Models specifically optimized for programming tasks, Safurai ensures robust performance in all its functions. The models are exclusively trained on synthetic data, and we prioritize not retaining or reusing user codebase data for enhancements. At Safurai, our commitment to "Transparency" goes beyond mere terminology; it reflects our genuine dedication to clear and open practices. This approach fosters trust and reliability among users, making Safurai a valuable asset in the world of software development.

Refact.ai is a cutting-edge AI-driven assistant that seamlessly integrates with your IDE, delivering smart code completion, instant code suggestions, and automatic refactoring to optimize the coding experience. Leveraging an AI model tailored to your specific codebase, Refact.ai customizes its recommendations to align with your team's coding style, significantly boosting productivity. Developers have the flexibility to adjust the assistant's functionalities to cater to their individual needs, making it an invaluable resource for personalized coding support. Compatible with all major IDEs and offering secure on-premise deployment, Refact.ai not only enhances code quality but also minimizes the time spent on tedious manual tasks, leading to quicker project turnaround times. Ultimately, this innovative tool transforms the way developers approach coding, fostering a more efficient and enjoyable workflow.

Tabby serves as a self-hosted, open-source AI coding assistant designed to enhance your development process through features like intelligent code completion, real-time suggestions, and seamless integration with your chosen integrated development environment (IDE). By deploying Tabby on your own servers, you gain the benefits of enhanced security and greater control over your codebase. It is designed to work with popular large language models (LLMs) such as CodeLlama, StarCoder, and CodeGen, which enables it to tailor its assistance to fit your individual coding style while providing accurate and context-aware support. No matter if you’re working independently or as part of a team, Tabby efficiently simplifies your coding tasks, reduces the likelihood of errors, and accelerates project delivery times. Its intuitive interface and customizable features distinguish Tabby as a vital resource for developers seeking to elevate their coding productivity. Overall, Tabby not only enhances coding efficiency but also fosters a more enjoyable and streamlined development experience.

Fine is a cutting-edge platform that harnesses artificial intelligence to assist startups by automating numerous processes within the software development lifecycle. It offers a range of AI-driven workflows that simplify tasks such as coding, debugging, testing, and code review, empowering teams to implement daily updates and quickly address pull requests. Fine can autonomously generate and implement code, evaluate pull requests, design tests, and tackle standard challenges without requiring constant supervision from developers. With seamless integration into GitHub, it supports asynchronous collaboration, making it particularly suitable for fast-paced startup settings. Furthermore, Fine provides real-time feedback and live previews, significantly boosting productivity and refining the overall development process. By utilizing these sophisticated capabilities, teams can devote more attention to strategic initiatives while the platform efficiently manages routine tasks, ultimately leading to a more streamlined development experience. This innovative approach not only enhances team efficiency but also fosters an environment where creativity and innovation can thrive.

We are thrilled to introduce Codestral, our first code generation model. This generative AI system, featuring open weights, is designed explicitly for code generation tasks, allowing developers to effortlessly write and interact with code through a single instruction and completion API endpoint. As it gains expertise in both programming languages and English, Codestral is set to enhance the development of advanced AI applications specifically for software engineers. The model is built on a robust foundation that includes a diverse selection of over 80 programming languages, spanning popular choices like Python, Java, C, C++, JavaScript, and Bash, as well as less common languages such as Swift and Fortran. This broad language support guarantees that developers have the tools they need to address a variety of coding challenges and projects. Furthermore, Codestral’s rich language capabilities enable developers to work with confidence across different coding environments, solidifying its role as an essential resource in the programming community. Ultimately, Codestral stands to revolutionize the way developers approach code generation and project execution.

Amazon Q stands out as the premier generative AI-assisted tool tailored for software development endeavors. It significantly improves the software development lifecycle by enabling agents to independently perform a range of tasks, including feature implementation, documentation, testing, code reviews, refactoring, and overseeing software updates. With the Amazon Q Developer, navigating the intricacies of the development process becomes remarkably easier. This tool possesses extensive knowledge of AWS, helping users optimize their cloud expenditures and resources while providing guidance on optimal architectural practices, analyzing operational issues, and addressing networking difficulties. Furthermore, Amazon Q Developer agents support the transformation of extensive enterprise workloads, facilitating the transition of .NET applications from Windows to Linux, modernizing mainframe applications, migrating and upgrading VMware workloads, and enhancing Java applications, all with the goal of streamlining processes and reducing costs. Its adaptability and wide-ranging capabilities render it an essential resource for developers aiming to boost the efficiency and productivity of their projects, ultimately leading to more successful outcomes.

Cline is an autonomous coding assistant seamlessly embedded in your IDE, capable of creating and modifying files, executing commands, browsing the internet, and more, all while ensuring you provide explicit consent at each step of the process. This tool is specifically designed to address complex software development issues in a systematic manner. With its ability to generate and alter files, navigate large codebases, access web resources, and execute terminal commands upon your approval, Cline offers a level of support that goes beyond basic code completion or technical help. In contrast to conventional AI scripts that function in isolated settings, this extension boasts an intuitive interface that necessitates your consent for every modification and command, thereby promoting a secure and user-friendly experience with autonomous AI. By utilizing such a system, developers are empowered to discover creative solutions while retaining complete oversight of their coding environment, thus enhancing productivity and innovation in their projects.

Aide proactively proposes solutions and identifies any missing files in the given context. Our agent effectively resolves linter errors while incorporating relevant context through LSP tools. You are encouraged to implement AI-driven enhancements during your coding activities. We utilize lightweight checkpoints integrated with VS Code (bypassing git) to allow for seamless reversion to previous versions in case of agent mistakes. Our aim is to make Aide function like a genuine engineer, fostering a collaborative programming environment. You can engage in discussions about a problem by tagging the necessary file(s) and then proceed with modifications, or you might start with a few changes and assess their consequences. Drawing inspiration from the spotlight feature on MacOS, we have introduced a floating widget that is activated with CMD + K, enabling you to quickly request changes based on any selected text. Furthermore, we offer a tool called Sidecar, which coordinates the preparation and sending of prompts to LLMs while providing access to various editor features, thus enhancing the entire coding experience. This innovative strategy effectively merges human intuition with machine productivity, making the programming process smoother and more efficient. Ultimately, our mission is to refine this collaborative dynamic, ensuring that developers can focus on creativity while leveraging AI assistance seamlessly.

Trae is a groundbreaking AI-powered integrated development environment (IDE) designed to revolutionize the experience of developers by facilitating seamless cooperation between human programmers and artificial intelligence. This collaborative model ensures that each task is handled by the most suitable participant, leading to heightened productivity and efficiency across projects. By merging human intuition with AI capabilities, Trae equips developers to launch their products to market more promptly and effectively. Moreover, this partnership cultivates a space where both creativity and technical skills can thrive in unison, ultimately enhancing the development landscape. With Trae, the future of development is not just about speed, but also about fostering innovative solutions.

The SWE-agent is an advanced AI-powered system designed to automate a wide range of activities, such as managing GitHub issues, performing cybersecurity tasks like Capture The Flag (CTF) challenges, and solving programming problems. By leveraging cutting-edge language models such as GPT-4 or Claude, it functions within secured computing environments to carry out its duties autonomously, offering tailored solutions for both developers and cybersecurity professionals. This adaptable tool serves various purposes, from improving software repositories to identifying security vulnerabilities and executing targeted operations. Developed through a partnership between researchers from Princeton and Stanford University, the SWE-agent showcases the fusion of machine learning with practical problem-solving in the fields of software engineering and cybersecurity. Its groundbreaking capabilities signify a substantial leap forward in the automation of intricate workflows, ultimately enhancing productivity for experts in these industries. Furthermore, the SWE-agent sets a new standard for the future of AI-assisted development and security measures.

Fynix operates as an advanced AI-powered platform designed to boost the efficiency of software development by offering intelligent coding assistance and agent-based code evaluations. This innovative tool integrates effortlessly with popular IDEs, including VS Code, and boasts features such as context-aware autocomplete, the ability to input natural language for code corrections and translations, and automatic visual representations of code flow. With its Code Assistant capability, Fynix empowers developers to write cleaner and more efficient code at a faster rate, while the upcoming Code Quality Agent aims to enhance bug detection and maintain coding standards. Supporting multiple programming languages and frameworks, along with compatibility with tools like Jira, Fynix emerges as a versatile solution that promotes better coding practices and encourages team collaboration. As developers continuously seek to refine their skills and produce high-quality code, Fynix has established itself as a vital partner in the evolving realm of software development, ensuring that teams can work more effectively together. Ultimately, the platform represents a significant advancement in the tools available to developers striving for excellence in their craft.

Visual Studio IntelliCode significantly improves the development experience by providing AI-enhanced assistance tailored to individual needs. By emphasizing the suggestions that are most likely to be relevant, it effectively streamlines the coding process. The recommendations are based on extensive data gathered from numerous open-source projects on GitHub, each with a minimum of 100 stars. When integrated with your current code, the completion suggestions are tailored to reflect best practices in coding. In addition to aiding in statement completion, IntelliCode offers signature assistance, presenting the most pertinent overload options in relation to the context. This tool not only delivers customized recommendations for your code but also simplifies the process of sharing insights among your team members. With the introduction of this preview feature, you can establish a team model that generates personalized suggestions for code beyond the open-source spectrum, which includes methods from your unique utility classes or specialized libraries. Moreover, by incorporating our build task into your development workflow, you can maintain up-to-date team completions that adapt to changes within the repository, ultimately fostering a more collaborative and efficient coding atmosphere. As a result, IntelliCode serves as an essential resource for developers seeking to enhance both their productivity and teamwork capabilities.

Code Llama is a sophisticated language model engineered to produce code from text prompts, setting itself apart as a premier choice among publicly available models for coding applications. This groundbreaking model not only enhances productivity for seasoned developers but also supports newcomers in tackling the complexities of learning programming. Its adaptability allows Code Llama to serve as both an effective productivity tool and a pedagogical resource, enabling programmers to develop more efficient and well-documented software. Furthermore, users can generate code alongside natural language explanations by inputting either format, which contributes to its flexibility for various programming tasks. Offered for free for both research and commercial use, Code Llama is based on the Llama 2 architecture and is available in three specific versions: the core Code Llama model, Code Llama - Python designed exclusively for Python development, and Code Llama - Instruct, which is fine-tuned to understand and execute natural language commands accurately. As a result, Code Llama stands out not just for its technical capabilities but also for its accessibility and relevance to diverse coding scenarios.

The premier open-source AI assistant allows you to design personalized autocomplete functions and chat interfaces by seamlessly linking various models to diverse contexts. By eliminating obstacles that disrupt your productivity during software development, you can maintain a smooth workflow. With a user-friendly plug-and-play system that integrates effortlessly into your entire tech stack, you can expedite your development process. Customize your code assistant to adapt as it gains new features and enhancements. Effortlessly autocomplete entire blocks of code or individual lines across multiple programming languages as you continue typing. You can inquire about files, functions, the full codebase, and more by associating relevant code or context. Additionally, highlight specific segments of code and utilize a keyboard shortcut to transform that code into easily understandable natural language, enhancing collaboration and comprehension. This innovative tool empowers developers to work more efficiently and creatively than ever before.

OpenAI o3 represents a state-of-the-art AI model designed to enhance reasoning skills by breaking down intricate tasks into simpler, more manageable pieces. It demonstrates significant improvements over previous AI iterations, especially in domains such as programming, competitive coding challenges, and excelling in mathematical and scientific evaluations. OpenAI o3 is available for public use, thereby enabling sophisticated AI-driven problem-solving and informed decision-making. The model utilizes deliberative alignment techniques to ensure that its outputs comply with established safety and ethical guidelines, making it an essential tool for developers, researchers, and enterprises looking to explore groundbreaking AI innovations. With its advanced features, OpenAI o3 is poised to transform the landscape of artificial intelligence applications across a wide range of sectors, paving the way for future developments and enhancements. Its impact on the industry could lead to even more refined AI capabilities in the years to come.

The o3-mini-high model created by OpenAI significantly boosts the reasoning capabilities of artificial intelligence, particularly in deep problem-solving across diverse fields such as programming, mathematics, and complex tasks. It features adaptive thinking time and offers users the choice of different reasoning modes—low, medium, and high—to customize performance according to task difficulty. Notably, it outperforms the o1 series by an impressive 200 Elo points on Codeforces, demonstrating exceptional efficiency at a lower cost while maintaining speed and accuracy in its functions. As a distinguished addition to the o3 lineup, this model not only pushes the boundaries of AI problem-solving but also prioritizes user experience by providing a free tier and enhanced limits for Plus subscribers, which increases accessibility to advanced AI tools. Its innovative architecture makes it a vital resource for individuals aiming to address difficult challenges with greater support and flexibility, ultimately enriching the problem-solving landscape. Furthermore, the user-centric approach ensures that a wide range of users can benefit from its capabilities, making it a versatile solution for different needs.