Grounding SWE-Agent Decisions in Architecture-0 Design: Navigating Unknown Unknowns through Physical Mapping

arXiv:2609.17221 · cs.SE, cs.AI · Submitted 2026-09-15 · Read on arXiv

cs.SE, cs.AI

Submitted: 2026-09-15

Updated: 2026-09-15

Comments: 51 pages, 13 figures, 18 tables. Preprint of a manuscript under review at ACM TOSEM

Code: https://github.com/donnemartin/system-design-primer

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Grounding — 83× in this paper · explained in 3 episodes
• Core — 54× in this paper · explained in 2 episodes
• Verification — 46× in this paper · explained in 2 episodes
• Consistency — 37× in this paper · explained in 3 episodes
• Physical Constraints — 14× in this paper · explained in 7 episodes
• Sycophancy — 14× in this paper · explained in 4 episodes
• Alignment — 11× in this paper · explained in 1 episode
• Ablation — 10× in this paper · explained in 1 episode
• Physical Mapping Guard — 10× in this paper
• Affordance — 8× in this paper · explained in 1 episode
• Calibration — 8× in this paper · explained in 7 episodes
• Hallucination — 8× in this paper · explained in 3 episodes
• Decoupling — 7× in this paper · explained in 2 episodes
• Generalizability — 7× in this paper · explained in 6 episodes
• Trace — 7× in this paper · explained in 2 episodes
• Benchmark — 6× in this paper · explained in 2 episodes
• Adversarial Prompting — 5× in this paper · explained in 1 episode
• Resource Constraints — 5× in this paper · explained in 3 episodes
• Service Level Agreement — 5× in this paper
• Topological Intermediate Representation — 5× in this paper
• Robustness — 4× in this paper · explained in 5 episodes
• Semantic Drift — 4× in this paper · explained in 3 episodes
• Entanglement — 3× in this paper · explained in 3 episodes
• Failure Modes — 3× in this paper · explained in 3 episodes
• Normalized Affordance Cost — 3× in this paper
• Prompt Engineering — 3× in this paper · explained in 4 episodes
• Reward Hacking — 3× in this paper · explained in 8 episodes
• Actionability — 2× in this paper · explained in 3 episodes
• Chain-of-Thought (CoT) — 2× in this paper · explained in 4 episodes
• Fidelity — 2× in this paper · explained in 2 episodes
• Generalization — 2× in this paper · explained in 13 episodes
• Generative AI — 2× in this paper · explained in 2 episodes
• Human-in-the-Loop — 2× in this paper · explained in 3 episodes
• Multi-Agent Framework — 2× in this paper · explained in 3 episodes
• Reinforcement Learning — 2× in this paper · explained in 4 episodes
• AI Alignment — 1× in this paper · explained in 2 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Absence of Human-in-the-Loop — 1× in this paper
• Abstraction — 1× in this paper · explained in 1 episode
• Adaptation — 1× in this paper · explained in 1 episode
• Aggregation — 1× in this paper · explained in 1 episode
• Archetype — 1× in this paper · explained in 1 episode
• Benchmarking — 1× in this paper · explained in 3 episodes
• Clustering — 1× in this paper · explained in 2 episodes
• Digital Twin — 1× in this paper · explained in 5 episodes
• Embodied AI — 1× in this paper · explained in 2 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Iterative Refinement — 1× in this paper · explained in 3 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Model-Agnostic — 1× in this paper · explained in 2 episodes
• Multi-Agent System — 1× in this paper · explained in 6 episodes
• Multi-agent system (MAS) — 1× in this paper · explained in 2 episodes
• Objective Function — 1× in this paper · explained in 2 episodes
• Ontology — 1× in this paper · explained in 2 episodes
• RAG — 1× in this paper · explained in 3 episodes
• Retrieval-Augmented Generation (RAG) — 1× in this paper · explained in 16 episodes
• Self-consistency — 1× in this paper · explained in 2 episodes
• Simultaneous Localization and Mapping — 1× in this paper
• Single Point of Failure — 1× in this paper
• Zero-Shot Generalization — 1× in this paper · explained in 5 episodes
• alpha — 1× in this paper · explained in 1 episode

Sources

• Do As I Can, Not As I Say: Grounding Language in Robotic Affordances
• Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback
• Demonstrating specification gaming in reasoning models
• Evaluating Large Language Models Trained on Code
• SWE-bench: Can Language Models Resolve Real-World GitHub Issues?
• Feedback Loops With Language Models Drive In-Context Reward Hacking
• OpenHands: An Open Platform for AI Software Developers as Generalist Agents
• SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineering
• Grounding LLMs in Scientific Discovery via Embodied Actions

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