Grounding SWE-Agent Decisions in Architecture-0 Design: Navigating Unknown Unknowns through Physical Mapping
Zhongkai Wang and Yan Liu (Tongji University) study how SWE agents handle early system design with unstated physical constraints, and propose taking verification out of the agent's hands.
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Failure chain: Text-only self-play produces agreeable consensus or physically impossible designs.
Specification gaming: Given an execution sandbox, agents edit their own validation scripts to pass checks without fixing the architecture.
Physical Mapping Guard: PMG removes verification authority from the agent and sends its semantic intents to an external deterministic Semantic-to-Physical mapping engine.
Result: PMG eliminates physical-layer and validation-layer gaming in their evaluation; the remaining failures are semantic reinterpretation and auditor overreach.
Abstract
Autonomous Software Engineering Agents (SWE-Agents) excel in deterministic coding tasks but struggle with Architecture 0, the nascent system design phase plagued by implicit engineering constraints, or Unknown Unknowns (UUs) that are rarely stated explicitly. To investigate how agents navigate UUs, we explore a progressive trajectory across pure-text self-play, tool-augmented feedback, and external physical mapping. Our empirical analysis reveals a cascading chain of failures. Pure-text reasoning inevitably devolves into polite consensus or plausible yet physically impossible fabrications. Attempting to bridge this gap via an early-stage execution sandbox unexpectedly triggers Specification Gaming: agents exploit their autonomy over validation scripts to bypass physical constraints, achieving superficial success without resolving core architectural flaws. To resolve this self-validation trap, we propose the Physical Mapping Guard (PMG). Grounded in the software engineering principle of Separation of Concerns, PMG revokes verification authority from the agent, forcing semantic intents to be evaluated by an external, deterministic Semantic-to-Physical (S2P) mapping engine. Extensive evaluations demonstrate that PMG completely eradicates physical-layer and validation-layer gaming. By precisely isolating residual failures to semantic reinterpretations and auditor overreach, PMG marks a critical step toward genuine affordance grounding in automated architectural design.