Is ChatGPT a Good Software Librarian? An Exploratory Study on the Use of ChatGPT for Software Library Recommendations

• URL: http://arxiv.org/abs/2408.05128v1
• Date: Fri, 9 Aug 2024 15:36:59 GMT
• Title: Is ChatGPT a Good Software Librarian? An Exploratory Study on the Use of ChatGPT for Software Library Recommendations
• Authors: Jasmine Latendresse, SayedHassan Khatoonabadi, Ahmad Abdellatif, Emad Shihab,
• Abstract summary: ChatGPT uses third-party libraries nearly 10% more often than human developers. 14.2% of the recommended libraries had restrictive copyleft licenses, which were not explicitly communicated by ChatGPT. We recommend that developers implement rigorous dependency management practices and double-check library licenses before integrating LLM-generated code into their projects.
• Score: 3.1911318265930944
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Software libraries play a critical role in the functionality, efficiency, and maintainability of software systems. As developers increasingly rely on Large Language Models (LLMs) to streamline their coding processes, the effectiveness of these models in recommending appropriate libraries becomes crucial yet remains largely unexplored. In this paper, we assess the effectiveness of ChatGPT as a software librarian and identify areas for improvement. We conducted an empirical study using GPT-3.5 Turbo to generate Python code for 10,000 Stack Overflow questions. Our findings show that ChatGPT uses third-party libraries nearly 10% more often than human developers, favoring widely adopted and well-established options. However, 14.2% of the recommended libraries had restrictive copyleft licenses, which were not explicitly communicated by ChatGPT. Additionally, 6.5% of the libraries did not work out of the box, leading to potential developer confusion and wasted time. While ChatGPT can be an effective software librarian, it should be improved by providing more explicit information on maintainability metrics and licensing. We recommend that developers implement rigorous dependency management practices and double-check library licenses before integrating LLM-generated code into their projects.

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