Thematic Analysis of Expert Opinions on the Use of Large Language Models in Software Development

ABSTRACT Large Language Models (LLMs) have gained popularity in recent years due to their ability to generate human‐like text and conduct context‐aware conversations in natural languages. This ability can be greatly beneficial for fields like software development, where LLMs can assist with tasks such as code generation, code review, and debugging. In this paper, thematic analysis has been performed on unstructured opinions obtained from 11 experts about the integration of LLMs in the field of software development to understand their benefits and limitations using two natural language processing (NLP) techniques: sentiment analysis and keyword extraction and analysis. Sentiment analysis suggests that most experts were optimistic and pragmatic about the use of generative artificial intelligence in software development, although some experts engaged in critical reflection. Keyword extraction and analysis mapped several keywords to pre‐defined themes, which highlighted benefits of LLMs such as improved code quality and enhanced developer productivity, as well as challenges such as the risk of over‐reliance, and privacy and security concerns.