Senatus -- A Fast and Accurate Code-to-Code Recommendation Engine
Fran Silavong,
Sean Moran,
Antonios Georgiadis
et al.
Abstract:Machine learning on source code (MLOnCode) is a popular research field that has been driven by the availability of large-scale code repositories and the development of powerful probabilistic and deep learning models for mining source code. Code-to-code recommendation is a task in MLOnCode that aims to recommend relevant, diverse and concise code snippets that usefully extend the code currently being written by a developer in their development environment (IDE). Code-to-code recommendation engines hold the prom… Show more
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