Knowledge-Guided Multi-Agent Framework for Automated Requirements Development: A Vision

TL;DR

This paper proposes KGMAF, a multi-agent framework guided by knowledge to automate requirements development, aiming to improve efficiency and accuracy over existing systems that focus mainly on coding tasks.

Contribution

It introduces a novel multi-agent framework with a detailed conceptual design for automated requirements development, addressing current gaps in automation systems.

Findings

Case study demonstrates KGMAF's potential in real-world scenarios.

Framework outlines specialized agents and artifact pool for improved requirements tasks.

Highlights future research opportunities in multi-agent requirements automation.

Abstract

This paper envisions a knowledge-guided multi-agent framework named KGMAF for automated requirements development. KGMAF aims to address gaps in current automation systems for SE, which prioritize code development and overlook the complexities of requirements tasks. KGMAF is composed of six specialized agents and an artifact pool to improve efficiency and accuracy. Specifically, KGMAF outlines the functionality, actions, and knowledge of each agent and provides the conceptual design of the artifact pool. Our case study highlights the potential of KGMAF in real-world scenarios. Finally, we outline several research opportunities for implementing and enhancing automated requirements development using multi-agent systems. We believe that KGMAF will play a pivotal role in shaping the future of automated requirements development in the era of LLMs.