Best AI Code Refactoring Tools for Mac - Page 2

Amazon Q Developer is a generative AI–powered coding assistant from AWS that helps developers accelerate the entire software development lifecycle. It integrates directly into popular IDEs like JetBrains, VS Code, Visual Studio, and Eclipse, providing real-time code suggestions, refactoring, documentation, and debugging assistance. Beyond coding, Amazon Q Developer supports agentic capabilities—autonomously performing tasks like feature implementation, testing, and modernization of applications. As an AWS-native expert, it helps optimize cloud resources, diagnose issues, and guide users through architectural best practices. The platform also enables seamless data and AI integration, allowing developers to build analytics and ML applications using natural language. With up to 80% faster development speed and 40% productivity gains, Amazon Q Developer delivers enterprise-grade intelligence directly inside the tools developers use every day.

Autonomous coding agent right in your IDE, capable of creating/editing files, running commands, using the browser, and more with your permission every step of the way. Cline can handle complex software development tasks step-by-step. With tools that let him create & edit files, explore large projects, use the browser, and execute terminal commands (after you grant permission), he can assist you in ways that go beyond code completion or tech support. While autonomous AI scripts traditionally run in sandboxed environments, this extension provides a human-in-the-loop GUI to approve every file change and terminal command, providing a safe and accessible way to explore the potential of agentic AI.

TRAE is an advanced AI-powered development environment that acts as a 10x engineering assistant for developers. It can autonomously understand project requirements, write code, debug issues, and deliver complete software solutions. TRAE integrates seamlessly into your workflow with intelligent features like real-time collaboration, contextual understanding, and predictive coding assistance. Its SOLO mode enables developers to build, test, and deploy entire applications with minimal input. Using Model Context Protocol (MCP), TRAE dynamically connects to tools, APIs, and external data to optimize performance and accuracy. Designed for speed, precision, and security, TRAE empowers developers to ship production-ready software faster than ever before.

SWE-agent is an advanced AI-powered tool designed to automate various tasks such as fixing GitHub issues, performing cybersecurity operations like Capture The Flag (CTF) challenges, and solving coding problems. By leveraging language models such as GPT-4 or Claude, it interacts with isolated computer environments to carry out tasks autonomously, providing highly customizable solutions for developers and cybersecurity professionals. The platform supports a wide range of use cases, from improving software repositories to identifying vulnerabilities, and even executing custom tasks. Developed by researchers from Princeton and Stanford University, SWE-agent offers a powerful way to integrate machine learning with practical problem-solving in both software development and security fields.

Fynix is an AI-powered platform designed to boost software development productivity through intelligent coding assistance and agent-based code reviews. It integrates directly into popular IDEs like VS Code and offers features such as context-aware autocomplete, natural language commands for code fixes and translations, and automatic code flow visualizations. Fynix’s Code Assistant helps developers write cleaner, more efficient code faster, while its upcoming Code Quality Agent will automate bug detection and enforce coding standards. With support for multiple programming languages and frameworks, and integrations with tools like Jira, Fynix is a versatile platform for improving coding efficiency and collaboration.

Visual Studio IntelliCode: AI-assisted development. IntelliCode saves you time by putting what you’re most likely to use at the top of your completion list. IntelliCode recommendations are based on thousands of open source projects on GitHub each with over 100 stars. When combined with the context of your code, the completion list is tailored to promote common practices. IntelliCode isn’t limited to statement completion. Signature help also recommends the most likely overload for your context. IntelliCode can provide recommendations based on your code and seamlessly share them across your team. With this preview feature, you can build a team model to provide recommendations on code that isn’t in the open source domain, such as methods on your own utility classes or domain specific library calls. Integrate our build task into your pipeline to keep your team completions up to date with repository changes.

Code Llama is a large language model (LLM) that can use text prompts to generate code. Code Llama is state-of-the-art for publicly available LLMs on code tasks, and has the potential to make workflows faster and more efficient for current developers and lower the barrier to entry for people who are learning to code. Code Llama has the potential to be used as a productivity and educational tool to help programmers write more robust, well-documented software. Code Llama is a state-of-the-art LLM capable of generating code, and natural language about code, from both code and natural language prompts. Code Llama is free for research and commercial use. Code Llama is built on top of Llama 2 and is available in three models: Code Llama, the foundational code model; Codel Llama - Python specialized for Python; and Code Llama - Instruct, which is fine-tuned for understanding natural language instructions.

OpenAI o3 is an advanced AI model designed to enhance reasoning capabilities by breaking down complex instructions into smaller, more manageable steps. It offers significant improvements over previous AI iterations, excelling in coding tasks, competitive programming, and achieving high scores in mathematics and science benchmarks. Available for widespread use, OpenAI o3 supports advanced AI-driven problem-solving and decision-making processes. The model incorporates deliberative alignment techniques to ensure its responses align with established safety and ethical guidelines, making it a powerful tool for developers, researchers, and enterprises seeking sophisticated AI solutions.

The leading open-source AI code assistant. You can connect any models and any context to create custom autocomplete and chat experiences inside the IDE Remain in flow while coding by removing the barriers that block productivity when building software. Accelerate development with a plug-and-play system that makes it easy to get started and integrates with your entire stack. Become a leader in AI by setting up your code assistant to evolve as new capabilities emerge. Continue autocompletes single lines or entire sections of code in any programming language as you type. Attach code or other context to ask questions about functions, files, the entire codebase, and more. Highlight code sections and press a keyboard shortcut to rewrite code from natural language.

The o3-mini-high model from OpenAI advances AI reasoning by refining deep problem-solving in coding, mathematics, and complex tasks. It features adaptive thinking time with adjustable reasoning modes (low, medium, high) to optimize performance based on task complexity. Outperforming the o1 series by 200 Elo points on Codeforces, it delivers high efficiency at a lower cost while maintaining speed and accuracy. As part of the o3 family, it pushes AI problem-solving boundaries while remaining accessible, offering a free tier and expanded limits for Plus subscribers.

Build apps faster with ML-powered coding companion. Accelerate application development with automatic code recommendations based on the code and comments in your IDE. Empower developers to use artificial intelligence (AI) responsibly to create syntactically correct and secure applications. Generate entire functions and logical code blocks without having to search and customize code snippets from the web. Stay focused and never leave the IDE, with real-time customized code recommendations for all your Java, Python, and JavaScript projects. Amazon CodeWhisperer is a machine learning (ML)–powered service that helps improve developer productivity by generating code recommendations based on their comments in natural language and code in the integrated development environment (IDE). Accelerate frontend and backend development by empowering developers with automatic code recommendations. Save time and effort by using CodeWhisperer to generate code to build and train your ML models.