GitHub Copilot, one of the first truly generative Ai code tools to be released, sent shockwaves throughout the software development community and beyond. Here was a tool that could intelligently produce lines of code out of thin air and with some accuracy never seen before. In this post, we’ll dive deep into the topic of ai code tools for .net development. We’ll explain what AI code tools are, their capabilities and limitations, how to use them, and more. We’ll also reflect on the future of coding in the era of generative AI code helpers like GPT-3 and GitHub Copilot.
What is AI code?
Ai code is code generated either wholly or partially using an AI coding tool or AI code generator. Ai code tools are trained with deep learning models like GPT-3 to understand natural language, coding patterns, and rules to produce valid, usable code. To generate AI code, you need to come up with a prompt or request that describes the problem clearly.
For example, you can ask an AI code tool to generate C# code for an ASP.NET webpage that adds two numbers and shows the results. More advanced AI tools can auto-generate code in your text editor or IDE based on context, upon request, or from written pseudocode. Below is an example of an AI coding tool asked to solve the problem in this example.
The Importance of Using AI in Software Development
Generative Ai code tools are the hottest topic in all software development circles. Thanks to advances in deep learning, today’s AI code tools are incredibly accurate and fast to the point that they cannot be ignored anymore.
Because it is early days, there has been, predictably, divided opinion and resistance to using code helpers in professional software development. However, many software developers are increasingly tapping into the power of AI coding tools to solve a variety of coding problems and to save development time and resources.
Perhaps the hottest and most disruptive technology in AI code is OpenAI’S GPT-3, released towards the end of 2022. GPT-3, Generative Pre-Trained Transformer 3, is the AI model behind Open Ai ChatGPT and several third-party AI code helpers. GTP-3 Is a large-scale language processing model trained on a large amount of code to improve accuracy.
AI use in coding will undoubtedly become standard practice as these models improve with continued training and usage.
Explanation of AI and .NET development
As one of the most popular software development frameworks today, .NET is heavily supported by most modern AI code tools. It’s also noteworthy that GitHub Copilot – one of the early Ai coding helpers- was developed by GitHub and OpenAI. Both these companies are essentially part of Microsoft or partially owned by Microsoft. Undoubtedly, the top Ai coding tools have been trained with corpus amounts of .NET code. They can produce more accurate code in .NET C# than in any other programming language.
You can use AI in .NET development in several ways, either through a third-party Ai code generation tool or with a predictive Ai code extension in your IDE. You can use AI in .NET development for code generation, code analysis, natural language processing, intelligent debugging, data manipulation, or even as an embedded feature to add AI functionality to your applications.
The most common way to utilize AI in .NET development is code generation, code prediction, or IntelliSense. AI tools can produce fairly accurate and relevant .NET code that can be edited and refined to be included in a project. Some advanced AI tools even further explain how the generated code and the logic behind it.
You can also use AI tools to analyze your own .NET code to identify patterns, detect common errors, e.g., syntax errors, and generate suggestions to improve your logic and structure (refactoring). Examples of AI code analysis tools that help you improve .NET code include CodeRush, Visual Studio IntelliCode, and ReSharper.
Ai code tools for .NET can also automate maintenance. An excellent example of such a tool is ML.NET, a machine learning tool you can use to analyze code in production and predict failures before they occur. ML. NET has enjoyed much success since its release. It is a must-use tool for .NET development, especially for complex legacy projects that are usually difficult to maintain.
Another disruptive application of Ai code tools is Natural language Processing. In .NET development, you can use AI tools like NRefactory and Roslyn to parse and understand any .NET code using normal or natural language instructions or queries. Previously, it would take .NET developers many hours to read a single file of .NET code to understand it, especially if it was written by someone else.
There are many other ways to take advantage of modern AI tools to make your work as a .NET developer easier. Ai tools keep improving as they are exposed to new use cases and training data. By using them in your projects, you also help improve them in one way or the other.
Is It Possible To Code With AI Tools In .Net Development?
Ai tools have been part of .NET development for quite a while but only became popular in recent years with the release of sophisticated generative and predictive AI code helpers like GitHub Copilot. You can use Ai tools in NET development in several ways, aside from generating or predicting code, as discussed above.
What Is AI Code Written in for .Net Development?
Any code generated using an Ai tool in .NET development is primarily written in C#, HTML, and CSS. For instance, you can instruct the Ai tool to generate boilerplate code for an ASP .NET application. It will generate the HTML, CSS, and backend logic using C#. However, Ai tools can generate or recognize code in JavaScript, C#++, and others supported in .NET core.
Benefits of Using AI Code Tools In .NET Development
There are several benefits associated with using various AI tools in software development. Here are some of them:
Ai Code Tools Improve Productivity
We all love writing code and seeing it deployed in the real world. However, we can also agree there is nothing fun about writing the same code pattern a thousand times or spending hours trying to debug poorly written code. Ai code tools can be handy when writing repetitive routine code in a software development project.
For example, .NET developers who write software for multiple platforms can avoid having to rewrite corpus amounts of code to make their deployed code work as expected on different platforms. Multi-platform programming in .NET requires you to be familiar with the nuances of each platform you are targeting, including framework and language differences, execution environments, etc. This is a time-consuming process and is usually not the best use of your time as a problem solver.
With the help of a modern AI coding tool, you can save a lot of time since the tool can automatically detect or predict platform-specific issues and rules for you. You can even write code for one platform using the AI tool to generate code compatible with each platform you are targeting.
More importantly, though on productivity, AI coding tools can reduce the work you need to develop software. You can use them to debug long code files, remove unnecessary code, solve dependency problems, generate comments and documentation, etc. Your job as a software developer will be solving complex problems and developing creative ideas to write better software.
Ai Code Tools Save On Costs
Small software development companies, startups, and businesses whose core business does not involve software development can save on labor costs associated with software development. On average, a small experienced software development team can cost a company upwards of $500,000 annually on salaries alone. Using AI coding tools in software development can help cut these costs significantly because tasks are automated.
Many experts, including ourselves, believe that introducing AI code tools will allow project owners to trim their software development workforce. Where a dozen or so developers were needed to develop a standard .NET application, a project owner can accomplish the same using three or fewer senior .NET developers who use AI code tools.
Another way to save on costs with AI coding tools is to reduce the number of non-coding staff in a project. Ai tools are getting extremely good at doing routine or mundane tasks in software development projects, such as code testing, debugging, and documentation. AI will significantly reduce the number of people needed to build and ship most .NET solutions, thus reducing costs.
You can use AI to Enhance code
There are a few things AI is better at, including producing clean, error-free code that also adheres to set standards. You can use AI coding tools to enhance human code in various ways, such as performance optimization, flow, documentation, structure, dependency tracking, syntax, compliance, resource allocation, etc.
In most instances, the best AI tools produce more efficient and accurate code than hand-coded code written by humans. AI code generation tools such as GitHub CoPilot, OpenAI GPT-3, Tabnine, CodeT5, Polycoder, and Cogramare can help you create code faster and more accurately in .NET, provided you have a clear idea of the problem you are trying to solve.
Ai code tools can also help your code review team generate valuable insights about code to make better-informed decisions. For instance, one can easily ask an AI code tool to analyze a code file, give insights on its structure, complexity, and number of dependencies, and even recommend improvements to make the code more efficient.
AI Tools Can Help Fast-Track Software Development
One direct advantage of using AI tools in software development is the time they will save your teams, allowing you to build and ship solutions quickly. Practically, you wouldn’t delegate all coding tasks to the AI coding tool if you want to maintain control over the project. However, your teams can delegate a chunk of their work to it and use it as a helper to complete routine tasks faster.
An excellent example of how you can use AI to fast-track coding in a software development project is boilerplate generation. While most IDEs and code editors have had this functionality for years, current AI tools take it to the next level. They can progressively add to the boilerplate to solve a problem. More importantly, the AI code tools like Google-backed AlphaCode can suggest code solutions to common and new problems based on your input or pseudo code.
The Best AI Code Generators For .Net Developers?
1. Ai Code Generation/Code Auto-completion Tools
These AI tools are used to generate .NET code from scratch based on queries or prompts from the developer.
CodeT5
CodeT5 is a transformer-based Ai model mainly used to understand natural language instructions and generate code. CodeT5 is an open-source AI coding tool developed by Salesforce. It works with .NET C# and many other popular languages.
PolyCoder
Same as other AI code tools, Polycoder can be used to generate code in a variety of development environments and languages. PolyCoder was developed by a team of researchers at Carnegie Mellon University. It uses the GPT-2 model developed by OpenAI. PolyCoder was trained with data based on at least 12 mainstream programming languages.
OpenAI Codex- ChatGPT
This advanced Ai code tool was recently embedded in OpenAI’s ChatGPT. It can be used by .NET developers to generate code for practically anything imaginable. This tool uses natural language processing and deep learning algorithms to generate high-quality code from user input.
GitHub Copilot
GitHub Copilot was one of the earliest coding tools to be powered by AI. It was developed by GitHub and can be embedded in Visual Studio, VsCode, or any other IDE or code editor to auto-generate .NET code intelligently based on context or upon request. It started as a free tool but is now available under a premium subscription model starting at $10 per month.
2. Enterprise-Level AI Code Tools
The following Ai tools are mainly used to develop .NET solutions on an enterprise level. They may include Ai code generators and other Ai tools designed to help with software development. Some also include tools to help .NET developers looking to add AI functionality to their applications
Azure Cognitive Services
Azure Cognitive Services is a suite of AI services you can use to automate software development in dotNET. This includes tools such as the Bot Framework, which allows you to create intelligent bots, and Computer Vision, which you can use to create applications that recognize objects in images.
ML.NET
ML.NET is a cross-platform machine learning framework you can use to build and train models inside dotNET. It supports a variety of ML algorithms and offers an easy-to-use API to integrate ML into .NET applications.
Microsoft Cognitive Toolkit (CNTK)
CNTK is a deep learning framework developed by Microsoft that you can use to create, train, and deploy models for .NET applications.
Amazon Machine Learning (ML)
Amazon ML is a cloud-based machine learning platform that provides an easy-to-use interface to build, train, and deploy models. It provides a range of tools to automate the process of training models.
Google Cloud Machine Learning Engine
Google Cloud Machine Learning Engine is a cloud-based machine learning platform with an easy-to-use interface to build, train, and deploy models. It provides a range of tools, including AutoML, to automate the process of training models.
What Are Some Of The Best Ways .Net Developers Can Use Ai To Write Better Code?
Despite their shortcomings, Ai tools are helpful if used as assistants to help you write better, well-structured, logical, accurate, and well-formatted code. The following are examples of specific ways you can use Ai Tools as a .NET developer:
Generate Clean C# Code with Ai
You can use Ai to generate clean code for well-known and routine programming problems in .NET, such as input validation, boilerplate generation, data processing, data manipulation, etc. Ai tools are generally faster and more accurate than human coders for well-defined programming tasks.
Use Ai Tools for Code Refactoring
Code refactoring has become easier for .NET developers working on complex projects and unfamiliar codebases. You can use Ai refactoring tools like CodeScene to analyze and improve an amount of code in .NET and ask it to suggest improvements with specific parameters such as syntax, logic, structure, and dependencies.
Detect Code Smells with Ai
Sometimes it’s hard for .NET developers, especially junior devs, to identify written code or what some refer to as code smells. Code smells are not bugs, but they can be warnings that the code may not be structured or written in the best way and could lead to problems down the line. Use an Ai code tool to identify and remove code smells as part of your code review process.
Use Intelligent Ai Code Prediction in Visual Studio
Visual Studio has pretty good code suggestions and IntelliSense functionality, but it can be improved with a dedicated prediction tool like GitHub Copilot. Ai-driven code prediction can make your work easier as it understands logic and detects patterns in code for better, more comprehensive suggestions.
Best Practices for Using AI Code Tools In .NET Development
While Ai tools are great in a development environment, you must use them responsibly. The following are some of the best practices to observe when using AI in .NET development:
Verify Generated Code
Don’t copy past code-generated code into your project and push it into production without verifying it. Just because Ai tools generate correct code doesn’t mean they don’t make mistakes that can negatively affect your applications. A recent study by Stanford-affiliated researchers found that most developers relying on Ai tools to write code are more likely to introduce security bugs. These tools are not a replacement for the experience and eye of a professional .NET developer.
Use trusted Ai code tools
As Ai code tools gain popularity, there are bound to be bad players entering the market to capitalize on the “naivete” and inexperience of junior devs who rely on Ai to write code. To avoid falling victim to such players, ensure the AI tools you use to code are genuine and authorized by your project manager or company. Watch for URL spoofing scams and fake Ai coding applications, even on mainstream platforms.
Be Transparent About the Use of Ai In Development
As a best practice, developers relying on Ai tools to develop .NET applications should disclose the same and explain how they were used and other details requested by the client. At the same time, being transparent about any Ai functionality embedded in the application to your end-users is important.
Integrate Ai Coding Tools With Existing Development Processes
If working in a team or as part of a software development company, use Ai while adhering to existing development processes and rules. Integrate the Ai tools into existing development processes and tools, such as source control, defect tracking, and build management. This will ensure the AI code is properly managed and tracked throughout development.
Future of AI Coding Tools In .NET Development
There is a general buzz about Ai coding tools in software development circles, especially with prominent players like OpenAI, Microsoft, Meta, Google, and IBM releasing their tools. , Ai tools will only improve and probably occupy a bigger space in many .NET software development projects. Only time will tell how Ai coding tools will co-exist with human developers.
Conclusion
Without a doubt, you have much to gain from using Ai tools as a .NET developer. Ai tools can help you improve the accuracy of your code, make adjustments to make the code more efficient, and so much more. For companies, Ai coding tools can help reduce costs and the time needed to build and deploy .NET applications or features to existing programs. However, at this stage, there is a need to understand that Ai tools have limitations and learn how to make the best of them without compromising the quality of your shipped code.
