arXiv AI
From Code to Requirements: Agentic Reverse Engineering of Business Rules at Enterprise Scale
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arXiv AI
Aug 24
BC-Bench: Evaluating Agentic Engineering in a Domain-Specific Language for ERP
BC-Bench is a new benchmark for assessing agentic engineering systems on the domain‑specific language AL used in Microsoft Dynamics 365 Business Central. It contains 101 manually curated tasks drawn from real Microsoft production repositories and evaluates not only code generation but also test creation and multimodal problem statements. The study shows that performance gaps between models are larger than those between different agent harnesses, and that gains on general‑purpose benchmarks do not reliably transfer to the AL domain.
arXiv AI
Jun 4
From Prompt to Process: a Process Taxonomy and Comparative Assessment of Frameworks Supporting AI Software Development Agents
arXiv:2606. 04967v1 Announce Type: cross Abstract: AI tools for programming are no longer just autocomplete or chat assistants: they organize themselves as development frameworks, with process, roles, artifacts and verification.
arXiv AI
Aug 24
SDAD: Spec-Driven Agentic Development for the AI-Native SDLC
The paper introduces Spec-Driven Agentic Development (SDAD), a framework that leverages large language models to ingest extensive functional requirement documents and repository context in a single workflow, turning specification quality into the engine for autonomous software delivery. SDAD blends disciplined upfront formalisation with rapid implementation, encompassing intent capture, machine‑readable specifications, agentic synthesis, and multi‑agent verification with human sign‑off. It positions AI‑code as a fourth production paradigm, compares it to traditional Waterfall and Agile approaches, and extends the model to team role evolution, quantitative governance metrics, and a staged migration blueprint for practical adoption.
arXiv AI
Jun 2
Bridging Requirements and Architecture: Multi-Agent Orchestration with External Knowledge and Hierarchical Memory
arXiv:2606. 01385v1 Announce Type: cross Abstract: Software architecture design is a critical yet inherently complex and knowledge-intensive phase that requires balancing competing quality attributes and adapting to evolving requirements.
arXiv AI
Jun 6
The End of Software Engineering: How AI Agents Are Fundamentally Restructuring the Software Paradigm
arXiv:2606. 05608v1 Announce Type: cross Abstract: For over half a century, software engineering has operated on a foundational premise: human engineers decompose problems, encode decision logic into static code, and manually adapt that code as requirements evolve.
arXiv AI
Jul 2
Cheap Code, Costly Judgment: A Case Study on Governable Agentic Software Engineering
arXiv:2607. 01087v1 Announce Type: cross Abstract: Generative AI is shifting software engineering from a practice organized around scarce implementation effort toward one organized around abundant, low-cost code production.