ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation

TL;DR

ReqBrain is a fine-tuned large language model tool that automates software requirements generation, improving accuracy and efficiency in requirements elicitation and specification through chat-based interactions.

Contribution

This work introduces ReqBrain, a novel AI-assisted tool employing fine-tuned LLMs for authentic and adequate requirements generation, with extensive evaluation of model effectiveness.

Findings

Zephyr-7b-beta achieved 89.30% Fl score

High human evaluation scores confirmed effectiveness

Fine-tuned LLMs can significantly aid requirements elicitation

Abstract

Requirements elicitation and specification remains a labor-intensive, manual process prone to inconsistencies and gaps, presenting a significant challenge in modern software engineering. Emerging studies underscore the potential of employing large language models (LLMs) for automated requirements generation to support requirements elicitation and specification; however, it remains unclear how to implement this effectively. In this work, we introduce ReqBrain, an Al-assisted tool that employs a fine-tuned LLM to generate authentic and adequate software requirements. Software engineers can engage with ReqBrain through chat-based sessions to automatically generate software requirements and categorize them by type. We curated a high-quality dataset of ISO 29148-compliant requirements and fine-tuned five 7B-parameter LLMs to determine the most effective base model for ReqBrain. The top-performing model, Zephyr-7b-beta, achieved 89.30\% Fl using the BERT score and a FRUGAL score of 91.20 in generating authentic and adequate requirements. Human evaluations further confirmed ReqBrain's effectiveness in generating requirements. Our findings suggest that generative Al, when fine-tuned, has the potential to improve requirements elicitation and specification, paving the way for future extensions into areas such as defect identification, test case generation, and agile user story creation.