Top 5 neural networks for programming

Neural networks are becoming a part of everyday developer practice, offering powerful tools for generating, analyzing, and optimizing program code. Artificial intelligence speeds up the development process and helps identify errors, improve the structure and readability of code, and master new programming languages. But their capabilities are not limited to this.

We will consider effective neural networks for programming, their key functions, and also describe real-life scenarios of application in the process of writing code.

How can neural networks help solve problems?

With the help of a neural network, you can automatically generate code fragments in different languages, optimize already written code, and find and fix errors. Artificial intelligence can easily solve routine tasks:

• writing templates;
• creating documentation;
• developing tests;
• parsing large amounts of data.

In addition, AI is able to explain complex code fragments and helps to learn new technologies, making training more accessible.

Neural networks are also used to improve the readability and architecture of programs, which is especially useful in team development. Thanks to integration with IDEs and online platforms, working with AI becomes intuitive and convenient. Thus, neural networks become real digital assistants for programmers of any skill level.

Programming and AI tools

AI tools in programming today are divided into several main categories.

Code generators

These are the most popular AI services. They allow you to quickly get a code fragment based on a text description of the task. Such tools can predict what the programmer is going to write and offer auto-completion of lines. This speeds up the work, especially when writing typical constructions. Thanks to these tools, the programmer can focus on the logic and architecture of the application, transferring routine and template tasks to artificial intelligence.

Modern generators can offer auto-completion options taking into account the context of the entire project. This is especially useful when working with large code bases and recurring patterns. AI can automatically complete a function, suggest a variable name, generate a loop or condition block, and also adapt the code to specific requirements.

Code analyzers and debuggers

Automatically analyze code, detect syntax and logical errors, warn about potential vulnerabilities and recommend how to improve the code structure. This is especially useful for ensuring the quality of a software product.

Code analyzers and debuggers are integrated into CI/CD pipelines and operate online. This allows teams to quickly find and fix errors before the code goes to production.

Optimizers and refactoring tools

Such neural networks help improve program performance, simplify logic, and make code more readable. They can suggest replacement of obsolete constructs, optimization of loops and conditions, as well as structural changes.

Documentation and test generation

AI can automatically create comments on code, explain its operation, and even generate unit tests that cover the main use cases of functions. This saves time and makes projects more maintainable.

Examples of tools:

1. ChatGPT — used to explain complex code fragments, generate unit tests, and refactor.
2. Codeium is a free AI assistant, similar to Copilot, with support for more than 70 programming languages.
3. GitHub Copilot is a built-in assistant for Visual Studio Code and other IDEs that offers code completion, comments on functions, and helps with writing documentation.

Also included here are TestGen AI — a tool for automatically generating tests based on code or specifications, and Tabnine, which can speed up coding by offering context-sensitive hints.

Training assistants

Some neural networks can not only write code, but also teach. They explain how a particular fragment works, offer alternative approaches, and help master new programming languages ​​or technologies. Training assistants can be used as a tutor — ask questions in free form, get step-by-step explanations, and even ask to analyze someone else's code. Many services offer interactive learning through dialogue, where AI guides the user from simple to complex.

Neural networks for programming: paid and free versions

Many of the listed tools are available in both free and paid versions. Free options usually provide basic functionality. They may limit the number of hints per day, the length of the generated code, and access to certain programming languages. In addition, free versions rarely have user support and the ability to customize the work for a specific project.

Paid versions, on the contrary, are focused on professional use. They offer more accurate generation, better understanding of the context, constant updates, improved integration with IDEs, and support from developers. Often, it is in the paid versions that the newest and most powerful features appear.

AI tools are no longer the future, but the present of programming. Correctly selected neural networks for programmers can save dozens of hours and significantly improve the quality of the code.

eXpress chatbots based on neural networks

Intelligent code generation and auto-completion

eXpress chatbots, using neural network technologies, are able to analyze developer requests and offer corresponding code fragments. This speeds up the process of writing programs and reduces the likelihood of errors.

Automated debugging and code analysis

eXpress technologies can automatically detect syntax and logical errors in the code, offering recommendations for eliminating them. This improves the quality of the software product and reduces the time spent on testing.

Documentation and test generation

Chatbots can automatically create code documentation and generate unit tests, which facilitates the process of maintaining and scaling projects.

Training and support

For beginner programmers, eXpress offers training materials and tips, helping to quickly master new technologies and programming languages.

Integration with popular development tools

Chatbots easily integrate with various development environments and version control systems, providing ease of use and increasing team productivity work.

Top 5 neural networks to help a programmer

Let's look at five neural networks that every programmer should try.

GPTunneL is an AI platform with support for popular services

GPTunneL combines the capabilities of such models as ChatGPT, Claude, and Grok. The service officially operates in Russia and provides access to many programming languages: from Python and JavaScript to Swift and Kotlin.

The platform acts as a universal AI tool for developers. Thanks to its flexible architecture and ready-made templates, GPTunneL is suitable for both individual and team work.

What it can do:

• generates code based on a text description of the task;
• finds and fixes errors;
• performs refactoring and optimization;
• explains software concepts and syntax;
• automatically writes documentation.

With its user-friendly interface and the ability to quickly switch between AI models, GPTunneL becomes a valuable assistant for both beginners and experienced developers. It is especially convenient when working with projects that require frequent generation of standard solutions and clear documentation.

The following advantages can be highlighted:

• support for the Russian language and Russian payment systems;
• ready-made assistants and templates in your personal account;
• free access with the possibility of expanding the functionality.

Claude – an intelligent assistant from Anthropic

This is a language model that is suitable for generating, analyzing and refactoring code. It supports many languages ​​and can be integrated into the workflow via API.

Claude, developed by Anthropic, is distinguished by special attention to security, context and a “soft” communication style. The model copes well with multi-step tasks and is actively used as an assistant for training and code review.

Features:

• helps in studying technologies, libraries;
• guarantees safe work with code, user data;
• takes into account the context of the entire conversation.

Claude is especially useful in projects where it is important to preserve data privacy and ensure predictable AI behavior. Thanks to the support of long context, the model works effectively with large code fragments and technical documentation.

GitHub Copilot – AI from OpenAI and GitHub

Copilot integrates with IDEs and offers real-time code completion. It is trained on a huge amount of open source code and is suitable for everyday work. With its help, you can speed up coding, reduce the number of routine operations and minimize the number of syntax errors. The tool actively adapts to the code style, context and programming language.

What it does:

• automatically completes lines and entire functions;
• generates code and tests based on comments;
• optimizes and simplifies the code base.

This tool significantly reduces the time spent on routine tasks and helps to focus on the logic of the application. It is especially useful in large projects where it is important to maintain a clean and understandable code base.

Advantages:

• support for many languages;
• deep integration with VS Code and other IDEs;
• ability to take into account the context of the entire project.

ChatGPT – Universal AI from OpenAI

ChatGPT is not just a chat, but a tool for code generation, error correction and training. It is especially useful for long dialogues and explanations of complex topics.

With natural language support, ChatGPT allows the developer to formulate queries in “human” language and receive accurate, contextual answers. This makes it a great assistant for both beginners and experienced specialists.

What it can do:

• writes code on request in natural language;
• explains syntax, algorithms and architectural decisions;
• helps to learn programming languages ​​and frameworks.

It is convenient to use both for quick reference and for deep analysis - from optimizing SQL queries to designing REST APIs. When combined with the code editor, ChatGPT turns into a real training and engineering platform.

Pros:

1. Intuitive interface;
2. A large amount of programming knowledge;
3. Integration into IDEs via API.

Tabnine - AI for code completion

Unlike universal models, Tabnine focuses on accurate code completion. Supports many languages ​​and works locally, ensuring privacy. This tool is great for developers who care not only about convenience, but also about data protection. Tabnine does not require a connection to the cloud (in the basic version) and minimally interferes with the workflow, adapting to the code style and the project.

Features:

• runs in the background in your IDE;
• offers accurate and contextual autocompletions;
• can learn from your code (in the Pro version).

Tabnine is especially appreciated in teams with high security and privacy requirements. It helps write code faster without violating internal standards and company rules.

Advantages:

1. fast and convenient integration;
2. support for a wide range of languages;
3. work locally without sending code to the cloud.

Conclusions

Neural networks are becoming a new tool in the arsenal of developers. But education and experience in software development do not lose their value - AI can make mistakes or generate incorrect code. A programmer's work does not end with the use of AI tools, so it is important to carefully check the results. However, AI tools save time and can cope with typical tasks and open up new opportunities for development.

Try different services and choose the right tool for your tasks.