Jul 2026· Anais do XI Workshop sobre Aspectos Sociais, Humanos e Econômicos de Software (WASHES 2026)· pp. 152-163· 0 citations· 19 references
TL;DR
GenAI tools are particularly valuable during requirements elicitation and specification, contributing to improved productivity and reduced operational effort, especially when addressing Functional Requirements (FRs).
Abstract
This paper investigates how Generative Artificial Intelligence (GenAI) grounded in Large Language Models (LLMs) are being employed to support activities within Requirements Engineering (RE). Based on interviews conducted with software engineering professionals, the findings indicate that GenAI tools are particularly valuable during requirements elicitation and specification, contributing to improved productivity and reduced operational effort, especially when addressing Functional Requirements (FRs). Despite these benefits, participants also reported important limitations, including sensitivity to prompt formulation, generation of overly generic outputs, and limited capability to adequately support Non-Functional Requirements (NFRs).
The state of the art in AI for requirements engineering research leading up to the transformation, before reviewing advances in LLMs, and two subsequent research areas: prompt programming and generalist SE agents, which combine multiple LLM advances to yield semi-autonomous processes that complete SE tasks.
Travis D. Breaux, Anmol Singhal· Requirements Engineering· 0 citations
Despite the rapid adoption of Large Language Models in professional software engineering, limited research has investigated how early career professionals develop effective AI assisted work practices during their transition into industry. We report findings from a mixed methods survey with 75 novice software engineers...
Julia Alencar, R. E. de Souza Santos, Ítalo Santos et al.· 0 citations
A systematic mapping study of 74 peer-reviewed primary studies on AI-based automated requirements elicitation published between 2021 and 2025, identified from five databases following PRISMA 2020 and classified by AI technique, textual source, elicitation activity, and application domain gives researchers and practitio...
Safaa Eltahier, S. Al-Ghuribi, Mawal A. Mohammed et al.· Information· 0 citations
The growing adoption of Large Language Models (LLMs) in Software Engineering has reinforced the expectation that coding activities can be largely automated. However, this perception may represent yet another historical search for a solution capable of eliminating the inherent challenges of software development. This ar...
AI-enabled software development tools (AI-devtools) are being industrially adopted under strong expectations of productivity gains, yet developers'experiences of such roll-outs are underexplored. Organizations commit budgets, evaluate staff, and revise practice on a partial picture, since the evidence base is mainly to...
Andreas Bexell, Rushali Gupta, L. Heander et al.· 0 citations
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