SEAIOct 11, 2022

Code Librarian: A Software Package Recommendation System

arXiv:2210.05406v23 citationsh-index: 3Has Code
Originality Synthesis-oriented
AI Analysis

This addresses the need for efficient library discovery for software developers, though it appears incremental as it builds on existing CodeBERT models for a specific application.

The paper tackles the problem of recommending open source library packages to shorten software development cycles by improving code quality and readability, using a CodeBERT-based model to analyze source code context and deliver relevant recommendations based on usage frequency, functionality similarity, and efficiency.

The use of packaged libraries can significantly shorten the software development cycle by improving the quality and readability of code. In this paper, we present a recommendation engine called Librarian for open source libraries. A candidate library package is recommended for a given context if: 1) it has been frequently used with the imported libraries in the program; 2) it has similar functionality to the imported libraries in the program; 3) it has similar functionality to the developer's implementation, and 4) it can be used efficiently in the context of the provided code. We apply the state-of-the-art CodeBERT-based model for analysing the context of the source code to deliver relevant library recommendations to users.

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