Best AI Code Refactoring Tools for Mac of 2025 - Page 2

Safurai, an AI-based IDE extension, is designed to aid developers by speeding up coding and debugging, documentation, and many other tasks. It acts as a virtual assistant and provides solutions and suggestions for any problems that may arise during software development. Safurai allows developers to improve their workflow and code quality. This makes the development process more efficient. Safurai AI is made up of a set of non-proprietary Large Language Models optimized for programming and performing all the functions. The models we use are trained with synthetic data only, we do not retain or reuse user codebase data for model improvement purposes. For Safurai, "Transparency" is not only a vogue word. We care a lot about transparency.

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.

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.

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.

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.

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.

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.

Amazon Q is the leading generative AI-powered assistant designed specifically for software development tasks. It enhances the entire software development lifecycle by allowing agents to autonomously carry out various functions, such as feature implementation, documentation, testing, code reviews, refactoring, and managing software upgrades. With Amazon Q Developer, the complexities of the development lifecycle are simplified significantly. This tool is well-versed in AWS, assisting users in optimizing cloud expenses and resources, offering insights on best architectural practices, examining operational problems, and resolving networking challenges. Additionally, Amazon Q Developer agents facilitate the transformation of large-scale enterprise workloads, including the porting of .NET applications from Windows to Linux, modernization of mainframe applications, migration and upgrades of VMware workloads, and Java enhancements, all aimed at streamlining operations and minimizing costs. Its versatility makes it an invaluable asset for developers looking to improve efficiency and effectiveness in their projects.

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.

OpenAI o3 is a cutting-edge AI model that aims to improve reasoning abilities by simplifying complex tasks into smaller, more digestible components. It shows remarkable advancements compared to earlier AI versions, particularly in areas such as coding, competitive programming, and achieving top results in math and science assessments. Accessible for general use, OpenAI o3 facilitates advanced AI-enhanced problem-solving and decision-making processes. The model employs deliberative alignment strategies to guarantee that its outputs adhere to recognized safety and ethical standards, positioning it as an invaluable resource for developers, researchers, and businesses in pursuit of innovative AI solutions. With its robust capabilities, OpenAI o3 is set to redefine the boundaries of artificial intelligence applications across various fields.

The o3-mini-high model developed by OpenAI enhances artificial intelligence reasoning capabilities by improving deep problem-solving skills in areas such as programming, mathematics, and intricate tasks. This model incorporates adaptive thinking time and allows users to select from various reasoning modes—low, medium, and high—to tailor performance to the difficulty of the task at hand. Impressively, it surpasses the o1 series by an impressive 200 Elo points on Codeforces, providing exceptional efficiency at a reduced cost while ensuring both speed and precision in its operations. As a notable member of the o3 family, this model not only expands the frontiers of AI problem-solving but also remains user-friendly, offering a complimentary tier alongside increased limits for Plus subscribers, thereby making advanced AI more widely accessible. Its innovative design positions it as a significant tool for users looking to tackle challenging problems with enhanced support and adaptability.