code completion

The previous articles from the series covered the following topics: In the first episode, we discussed general code completion scenarios.The second episode was devoted to the difficulties of heuristics-based implementation and explaining the necessity of machine learning.In the third episode, we described the data we collect from IDEs to train the completion ranking algorithm. We would like

As we discovered in the second installment of this series, a modern code completion system needs machine learning to rank the suggestions most effectively. Machine learning has one thing in common with human learning: it requires data to extract knowledge. There are many aspects to that process. We use so-called supervised learning for code completion, and that involves feeding the algorithm a

Why not order by what’s logical? I don’t understand.From a bug report In episode 1, we learned about the principal components of the code completion system and discussed its usage patterns and quality requirements. Today, let’s look into what reasons we have to employ machine learning aside from just following the hype. It’s a tough decision to make to replace “code that works” with a machi

Have you ever wondered what happens in the IDE when you start typing a new word and the code completion popup appears? The popup that’s displayed uses machine learning under the hood by default for Java, Python, Ruby, JavaScript, TypeScript, Go, and Scala. This technology can also be manually enabled for other languages in the settings: We would love to hear your feedback on ML-based comple