QUARE: Multi-Agent Negotiation for Balancing Quality Attributes in Requirements Engineering
Haowei Cheng, Milhan Kim, Foutse Khomh, Teeradaj Racharak, Nobukazu Yoshioka, Naoyasu Ubayashi, Hironori Washizaki

TL;DR
QUARE introduces a multi-agent negotiation framework for requirements engineering that explicitly manages conflicts among quality attributes, improving compliance, semantic preservation, and verifiability in automated RE processes.
Contribution
The paper presents a novel multi-agent negotiation approach with explicit conflict resolution for requirements engineering, enhancing automation and quality assurance over existing LLM-based methods.
Findings
Achieves 98.2% compliance coverage, 105% improvement over baselines.
Maintains 94.9% semantic preservation, surpassing previous methods.
High verifiability score of 4.96 out of 5.
Abstract
Requirements engineering (RE) is critical to software success, yet automating it remains challenging because multiple, often conflicting quality attributes must be balanced while preserving stakeholder intent. Existing Large-Language-Model (LLM) approaches predominantly rely on monolithic reasoning or implicit aggregation, limiting their ability to systematically surface and resolve cross-quality conflicts. We present QUARE (Quality-Aware Requirements Engineering), a multi-agent framework that formulates requirements analysis as structured negotiation among five quality-specialized agents (Safety, Efficiency, Green, Trustworthiness, and Responsibility), coordinated by a dedicated orchestrator. QUARE introduces a dialectical negotiation protocol that explicitly exposes inter-quality conflicts and resolves them through iterative proposal, critique, and synthesis. Negotiated outcomes are…
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Taxonomy
TopicsSoftware Engineering Techniques and Practices · Advanced Software Engineering Methodologies · Software Engineering Research
