Large Language Models for Early-Stage Software Project Estimation: A Systematic Mapping Study

Accurate estimation of software project characteristics during the early stages of development remains a constant challenge in software projects. Recent research suggests that large language models (LLMs) offer new opportunities to support such estimation tasks through their ability to interpret natural language specifications and extract contextual information from project descriptions. This paper presents a mapping study providing an overview of research on the applications of LLMs in early software project estimation. Thirty primary studies were systematically identified and categorised to examine estimation targets, used models, reference and supportive techniques, as well as applied evaluation measures. The obtained results provide insights into the methodological considerations, limitations, and challenges associated with LLM-based estimation approaches. The obtained findings inform both researchers and practitioners about the current state and potential of LLMs for supporting early-stage software project estimation.