Combining Code Embedding with Static Analysis for Function-Call Completion

Understand

Code completion is an important feature of integrated development environments (IDEs).

• It allows developers to produce code faster, especially novice ones who are not fully familiar with APIs and others code.
• Previous works on code completion have mainly exploited static type systems of programming languages or code history of the project under development or of other projects using common APIs.
• In this work, we present a novel approach for improving current function-calls completion tools by learning from independent code repositories, using well-known natural language processing models that can learn vector representation of source code (code embeddings).