AI gives software development tools a boost
The sudden acceleration in digital transformation caused by the COVID-19 pandemic revealed how unprepared most businesses were. One of the biggest problems they still face is the “app gap,” the lack of applications that end users need to do their jobs effectively. Low-code and no-code tools go some of the way to filling the gap, with UI builders and robotic process automation, but there’s still a lot to do.One option is to use machine learning to improve developer productivity. We’re already using basic rules-based tools to provide code completion and help expose methods, so why not go further and build on a massive data set of public code to share how common design patterns are applied, what algorithms are used in what contexts, and how developers take advantage of public APIs?To read this article in full, please click here
The sudden acceleration in digital transformation caused by the COVID-19 pandemic revealed how unprepared most businesses were. One of the biggest problems they still face is the “app gap,” the lack of applications that end users need to do their jobs effectively. Low-code and no-code tools go some of the way to filling the gap, with UI builders and robotic process automation, but there’s still a lot to do.
One option is to use machine learning to improve developer productivity. We’re already using basic rules-based tools to provide code completion and help expose methods, so why not go further and build on a massive data set of public code to share how common design patterns are applied, what algorithms are used in what contexts, and how developers take advantage of public APIs?
