Clean up your code using AI with DeepCode
Keep your code squeaky clean with DeepCode, a tool that analyzes your GitHub repos with the power of AI. Fix problems, improve flow, and make better code, all with the help of an AI engine.
No one likes having to clean up code. That’s why we have spaghetti code, inherited from programmers a decade ago. But there are options available, beyond actually going through line after line of code and tidying everything up. Enter DeepCode.
So, how does it work?
DeepCode reads your GitHub repositories and analyzes them based on the latest research in machine learning and programming languages. More specifically, it runs your code through a number of tools like JS Nice, Nice 2 Predict, and Deguard, checking your code against over 250,000 coding rules. Then, the built in AI highlights any problems with the code and suggests a few changes.
But don’t be fooled, it’s not just a debugger. This machine learning tool provides rich coverage over all sorts of issues. Thanks to the massive corpus of examples, DeepCode has a solid foundation to not only find errors in your code repos that you might have missed, but also make trenchant suggestions to improve things.
“We built a platform that understands the intent of the code,” said Boris Paskalev to TechCrunch. “We autonomously understand millions of repositories and note the changes developers are making. Then we train our AI engine with those changes and can provide unique suggestions to every single line of code analyzed by our platform.”
DeepCode is available for a free 30-day trial. There are also several tiers available, including a free plan for GitHub OpenSource projects. A personal plan will set a developer back about $6 a month, with enterprise plan pricing upon request.
For more information about DeepCode, check out their website here.