Alfonso Cannavale, Antonio Della Porta, Gianmario Voria, Gilberto Recupito, Maria Teresa Baldassarre, Gemma Catolino, Fabio Palomba, Andrea De Lucia, Stefano Lambiase · 2026 · arXiv (Cornell University)
DOI: 10.48550/arxiv.2610.29741 · cited by 0 works (OpenAlex) · open-access PDF
لا يزال البحث في التقنيات التقنية المطلوبة (RE) موجودًا يتناول أبعادًا واسعة من أنظمة الذكاء الاصطناعي ومتعددة الأبعاد، ولكن لا توفر أي بيانات عملية لتقنيات الذكاء الاصطناعي، والتي لا يمكن توقع سلوكها غير المحدد في وقت التصميم. لمعرفة كيف تنتهي الأجهزة في الواقع، قمنا بتطبيق نظرية التقنية المطلوبة الاجتماعيّة على 36 مقابلات فصليّة مع الممارسين، مما يجعل تجميع البيانات والتحليلات المرتبطة بتجميع البيانات واكتشافها من خلال دورة محددة من أربعة أنواع من النشاطات: تحتاج الأطراف إلى مساحة العملية، وبناء الممارس، والتحكم في سلوكها، وتحديد ما ي
Machine translation (Meta M2M100); the English original follows.
How teams engineer requirements for systems built around Generative AI (GenAI) Agents remains empirically uncharted. Existing Requirements Engineering (RE) research mainly addresses AI and ML-based systems broadly but provides no process account for agentic systems, whose non-deterministic behavior cannot be anticipated at design time. To understand how teams actually proceed, we applied Socio-Technical Grounded Theory across 36 semi-structured interviews with practitioners, interleaving data collection and analysis so that emerging findings drove our theoretical sampling and shaped successive rounds of coding. The result is Behavioral Agent Requirement Discovery (BARD), the process theory of RE for GenAI Agents. BARD holds that requirements are not fixed up front but discovered through a recurring cycle of four activities: teams scope the need, build the agent, observe its behavior, and revise what they ask for. Through this four-phase loop, the requirement evolves from a fixed specification towards behavioral and evaluation criteria. Four tensions drive transitions between phases, and two conditions frame the loop. BARD provides researchers with a framework for iteratively refining RE workflows, while giving practitioners a structured basis to embed into their development processes.
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Topics: Generative grammar, Interleaving, Computer science, Frame (networking), Process (computing), Scope (computer science)
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