Microsoft Corporation
Neural code completion via re-ranking
Last updated:
Abstract:
A code completion system uses neural components to rank the unordered list of code completion candidates generated from an existing static analyzer. The candidates represent the next sequence of tokens likely to complete a partially-formed program element as a developer is typing in a software development tool. A re-ranking component generates a ranked order of the candidates based on a context embedding of the code context and candidate embeddings of the candidates, where both embeddings are based a common token encoding.
Status:
Grant
Type:
Utility
Filling date:
15 Jun 2020
Issue date:
19 Apr 2022