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
现有要求工程(RE)研究主要针对人工智能和基于ML的系统广泛,但不提供对代理系统的过程报告,其非决定性行为在设计时无法预测。为了了解团队实际如何进行,我们在36次半结构面试中应用了社会技术基础理论(BARD),与从业人员进行了半结构面试,交叉数据收集和分析,以便新发现驱动我们的理论样本采集并塑造了连续的编码轮回。结果是行为代理要求发现(BARD),REAI代理人的过程理论。BARD认为要求不是固定在前面,而是通过四个活动的特定循环进行发现:团队需要范围,构建代理人,对其行为进行转换,并对两者之间的紧张性进行审查。
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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