Best AI Coding Assistants for Go - Page 3

DryRun Security has been built from our experience training 10,000+ developers and security professionals in application security testing and building security products at GitHub and Signal Sciences. From our experience, one thing is missing from all tools on the market today: security context for developers. Developers make code changes all day, every day. They need a security tool that provides security context to help them move faster and safer. Security code reviews often slow down the development team and happen too late in the development pipeline. Developers need security context right when a pull request is opened, so they can know the impact of the code change that's getting merged. Until now, most security testing has taken a generic approach that frustrates developers with repetitive alerts or inaccurate results.

Augoor transforms static code into dynamic knowledge, enabling teams to navigate, document, and optimize complex systems effortlessly. By extracting structures, relationships, and context, Augoor builds a living knowledge graph that accelerates the development lifecycle. Its AI-driven code navigation tool accelerates new developer productivity, integrating them into projects from day one. Augoor reduces maintenance efforts and enhances code integrity by pinpointing problematic code segments, saving costs, and reinforcing your codebase. It automatically generates clear, updated code explanations, preserving knowledge, especially for complex legacy systems. The AI navigation system cuts down time spent searching through code, allowing developers to focus more on coding, speeding up feature development, and fostering innovation in large codebases. Augoor's advanced AI-driven visualizations uncover hidden patterns, map complex dependencies, and reveal critical relationships.

Mistral Code is an AI-powered coding assistant designed to enhance software engineering productivity in enterprise environments by integrating powerful coding models, in-IDE assistance, local deployment options, and comprehensive enterprise tooling. Built on the open-source Continue project, Mistral Code offers secure, customizable AI coding capabilities while maintaining full control and visibility inside the customer’s IT environment. It supports over 80 programming languages and advanced functionalities such as multi-step refactoring, code search, and chat assistance, enabling developers to complete entire tickets, not just code completions. The platform addresses common enterprise challenges like proprietary repo connectivity, model customization, broad task coverage, and unified service-level agreements (SLAs). Major enterprises such as Abanca, SNCF, and Capgemini have adopted Mistral Code, using hybrid cloud and on-premises deployments.

Codey accelerates software development with real-time code completion and generation, customizable to a customer’s own codebase. This code generation model supports 20+ coding languages, including Go, Google Standard SQL, Java, Javascript, Python, and Typescript. It enables a wide variety of coding tasks, helping developers to work faster and close skills gaps through: Code completion: Codey suggests the next few lines based on the context of code entered into the prompt. Code generation: Codey generates code based on natural language prompts from a developer. Code chat: Codey lets developers converse with a bot to get help with debugging, documentation, learning new concepts, and other code-related questions.

CodeGemma is a collection of powerful, lightweight models that can perform a variety of coding tasks like fill-in-the-middle code completion, code generation, natural language understanding, mathematical reasoning, and instruction following. CodeGemma has 3 model variants, a 7B pre-trained variant that specializes in code completion and generation from code prefixes and/or suffixes, a 7B instruction-tuned variant for natural language-to-code chat and instruction following; and a state-of-the-art 2B pre-trained variant that provides up to 2x faster code completion. Complete lines, and functions, and even generate entire blocks of code, whether you're working locally or using Google Cloud resources. Trained on 500 billion tokens of primarily English language data from web documents, mathematics, and code, CodeGemma models generate code that's not only more syntactically correct but also semantically meaningful, reducing errors and debugging time.