Best AI Tools for Software Developers: Turbocharge Your Coding in 2024

The world of software development is evolving at neck-breaking speeds. It seems like every day, there’s a new AI tool promising to change the game. And let’s face it, keeping up with all the new tools can be exhausting! But amidst the chaos, one trend looks crystal clear: AI is here to stay, and it’s changing the way we code – for the better.

According to a recent survey by Stack Overflow, a whopping 80% of developers believe that AI will significantly impact their work in the next five years. Although AI isn’t quite there yet to be able to replace us developers, it doesn’t mean we can just sit back and wait till it does. If you’re not leveraging AI tools in your development, you’re at risk of getting left behind as average developers learn how to be 10X developers.

Don’t worry though, this article will help you start the journey of becoming a 10X developer. Here’s a massive opportunity to boost your productivity and efficiency. In this article, we’ll delve into the exciting world of AI tools for software developers, exploring the top solutions that can help you write better code, faster, and with fewer headaches.

AI-Powered Code Completion: Your Coding Copilot

When I first heard about AI-powered code completion, I was astounded! I’ve never seen a tool that can generate whatever snippet of code you want. My first AI tool was ChatGPT, and I was able to do some amazing things with it. I could generate just about any function in any programming language. No matter how complex the code was, ChatGPT was still able to produce the code at lightning speeds. Of course, the code itself was usually accurate about 99% of the time, the logic and implementation of the code was not always the best fit for my particular app. However, the use of AI to write the initial code saved me a good hour or two of programming. 

Since then, I’ve used other AI tools to code and my favorite is Copilot from GitHub. My go-to IDE is visual studio code, and the Copilot extension transformed the way I develop. Now instead of spending hours to code up a new feature in an app, I can perform the same feat in less than 45 minutes. Of course, there are times when the AI doesn’t quite get what I’m going for or forgets the business requirements of the app, but I find it much easier and even more rewarding when I focus my efforts on prompt engineering rather than writing up the solution myself. 

Make no mistake, code completion tools do not replace human developers. A human is still needed to prompt the AI, review the code for errors, and also to piece together the software. Think of AI as your own personal junior developer who can write in any language but needs direction on what to do and how it’s all connected. 

If you’re itching to try this out for yourself, check out this list of AI code completion tools below:

GitHub Copilot

An AI pair programmer that suggests code completions as you type, directly within your IDE. Copilot excels at providing context-aware suggestions, even generating entire functions based on your comments or code patterns. It offers seamless integration with Visual Studio Code and other popular editors.
Pricing: Free trial available, then $10/month for individuals or $19/user/month for businesses.

ChatGPT

A versatile language model capable of generating code snippets, explanations, and even debugging assistance. ChatGPT is best for providing high-level guidance and code examples, especially when exploring new concepts or troubleshooting. However, it may not be as contextually accurate as tools like Copilot for in-editor completions.
Pricing: Free access with limitations, ChatGPT Plus subscription for $20/month offers faster response times and priority access to new features.

Tabnine

An AI code completion tool that learns from your code patterns and provides suggestions across a wide range of languages and IDEs. Tabnine is known for its speed and accuracy, offering completions even in less common languages.It also boasts robust customization options to tailor suggestions to your preferences.
Pricing: Free plan with limited features, Pro plan for $12/month offers full access to capabilities.

Amazon Q Developer

Amazon Q Developer is an AI-powered coding assistant that provides real-time code recommendations directly within your IDE. Building on the strengths of its predecessor, CodeWhisperer, Amazon Q excels at suggesting code snippets that are highly relevant to the AWS ecosystem, making it a powerful tool for cloud-based development. Additionally, it offers comprehensive security scans to identify and remediate potential vulnerabilities in your code​.
Pricing: Free plan with limited features; Pro plan for $19/user/month offers advanced tools and enterprise integration.

Just remember, these tools are meant to augment your skills, not replace them. Use them as a springboard for your own ideas, not a crutch. Stay critical and don’t let the AI do all the thinking.

AI-Driven Debugging: Squash Bugs Before They Hatch

We’ve all seen this: a missing semicolon, a render error whose origins are unknown, or a well thought out function with several logic conditions but missed one rare use case that could break the code and give the user a nasty red-colored error page. Remember those late nights staring at the screen, wondering why your code’s not working? Only to realize it just needs to import one component without the brackets (even though all the other imports were done with brackets). Yeah, those days are over for me.

I recently tried out Snyk on a project, and it caught a subtle null pointer exception in a part of my code I’ve already spent hours writing. You know what would’ve happened in the past? I would publish this code, enjoy a can of Celsius, and consider the work done. Then a few days later, a user sends an email complaining that the app crashes, and I’m stuck wondering how that happened. I would start looking over crash logs, inspecting my latest changes, and scouring through articles on Stack Overflow before I realized the issue (usually a very minute change to the code). AI saved me a day’s work of debugging! 

If you’re ready to try this out for yourself, here’s a quick overview of some AI debugging tools:

Snyk

An AI-based security tool that scans your code for vulnerabilities and provides detailed explanations and remediation advice. Snyk is particularly useful for identifying and fixing security issues in open-source dependencies.
Pricing: Free plan with limited scans, paid plans available for larger teams and projects.

Embold

An AI-driven code analysis platform that helps you understand and improve the overall quality of your codebase. Embold is excellent at visualizing complex code structures and identifying areas for refactoring.
Pricing: Free plan with limited features, paid plans starting at €6.72 /month available for more extensive analysis and collaboration.

So, if you’re tired of playing hide-and-seek with bugs, give AI-driven debugging a shot. It might just save you on your next project. Plus, less time debugging means more time building cool stuff. And isn’t that why many of us got into coding in the first place?

AI Tools for Automated Testing: Ensure Code Quality with Ease

I was never a fan of testing. I just want to publish my work right away after developing. But I first have to spend some days manually coming up with test cases for every possible scenario? 

Testing is a tedious process that cannot be overlooked. The quality of testing is one of the key differences between a junior and senior developer. You have to test your app before making it public, otherwise you put your career on the line! But this doesn’t have to be a long tedious process; not anymore. 

With AI, there’s now tools that can automate the process of testing software. However, there’s one thing I learned – AI testing isn’t about replacing human testers. It’s about freeing them up to do the creative, complex testing that machines can’t handle. It’s like having a tireless assistant who takes care of the grunt work while you focus on the tricky stuff.

If you’re ready to take your testing to the next level, give these AI-powered tools a try:

Testim.io

An AI-powered test automation platform that creates, executes, and maintains tests across various platforms.Testim.io is particularly adept at generating test cases for complex user flows and handling dynamic web applications.
Pricing: Free plan, higher-tier plans require direct contact for custom pricing.

Applitools

An AI-powered visual testing and monitoring platform that helps ensure the visual integrity of your applications. Applitools excels at prioritizing test cases based on risk and impact, optimizing your testing efforts.
Pricing: Free plan for single user, paid plans require direct contact for custom pricing.

Functionize

For a more enterprise level, Functionize is an AI-powered end-to-end testing platform that uses machine learning to create, execute, and maintain tests. Functionize is known for its ability to learn from test results and improve its accuracy over time.
Pricing: Contact for custom pricing.

Some people think that testing is the bane of programming (or was it commenting… I guess they both are). But it doesn’t have to be this way. You don’t have to spend hours of your time on testing; and free up time for coding, designing, learning new software development skills, or playing video games. 

AI-Enhanced Code Review: Collaborate and Improve Code Quality

AI-enhanced code review has been a real eye-opener for me. I first tried an AI code review tool called DeepSource as a test for a mock code review. It flagged inconsistencies, pointed out potential bugs, and even suggested improvements. 

But here’s what really blew my mind: the AI didn’t just find problems, it explained them. There was this one time it flagged a piece of code as a potential memory leak. Not only did it point it out, but it also explained why it was an issue and suggested a fix. It was like having a senior developer giving you personalized coding lessons.

The coolest part? These AI tools are actually learning from your codebase. I noticed that after a few trials, the suggestions became more tailored to the fake project’s specific needs. It started catching issues that were unique to our architecture.

If you’re looking to elevate your code quality and streamline your review process, AI-enhanced code review tools can be a game-changer. Here’s a look at some of the best options available:

Amazon CodeGuru Reviewer

A subservice under Amazon CodeGuru, CodeGuru Reviewer leverages machine learning to identify potential bugs, security vulnerabilities, and performance issues in your code. CodeGuru Reviewer excels at providing context-aware suggestions and recommending best practices specific to your codebase.
Pricing: Pay-as-you-go model, with charges based on the number of lines of code analyzed.

Code Climate

An AI-powered static code analysis tool that provides automated code reviews and detailed analytics. Code Climate is particularly helpful for identifying code hotspots, suggesting quality improvements, and highlighting technical debt within a project.
Pricing: Free plan for open-source repositories with unlimited users; free startup plan for private repositories up to 4 users, then $16.67/user/month for the team plan.

DeepSource

An AI-powered code review tool that uses machine learning to identify potential bugs, security vulnerabilities, and performance issues. DeepSource is known for its ability to catch subtle errors and provide actionable insights for improving code quality.
Pricing: Free open-source projects, paid plans for private repositories starting at $8/user/month.

Codacy

An AI-powered static code analysis platform that automates code reviews and helps enforce code quality standards. Codacy is particularly useful for teams that want to establish and maintain consistent coding practices.
Pricing: Free plan with limited features, paid plans starting at $15/user/month.

If you’re on a dev team that loves to argue about code quality or can’t make their mind on what’s the best way to display this table, then try one or more of these tools. AI-enhanced testing can cut the hours away from that dreadful zoom session on Mondays.

Conclusion

The AI revolution is transforming the software development landscape, offering developers a wealth of powerful tools to enhance their productivity, efficiency, and code quality. From code completion and debugging to testing and code review, AI is poised to become an indispensable part of every developer’s toolkit.

So, what are you waiting for? Embrace the power of AI and unlock your full coding potential in 2024 and beyond! Remember, the future of software development is intelligent, and those who adapt will thrive.