Large Language Models in Qualitative Software Engineering Analysis

This podcast is about a research paper that investigates the use of Large Language Models (LLMs) in qualitative data analysis, particularly within software engineering. A systematic mapping study analysed 21 research papers exploring how LLMs are employed for tasks like coding and thematic analysis. The study identifies several benefits, including increased efficiency and support for novice researchers, but also highlights limitations such as inconsistent outputs, ethical concerns, and the inability of LLMs to fully capture nuanced perspectives. The authors conclude that while LLMs are a promising tool, human expertise remains crucial for accurate data interpretation, and recommend strategies for responsible LLM integration in research workflows. The paper offers recommendations for researchers using LLMs, including guidelines for prompt engineering, data protection, and maintaining human oversight.