Native Probes on Demand: Agent-Generated Reference Implementations for Layer-Bisection Debugging in Cross-Platform Apps

Abstract

: Cross-platform application frameworks promise a single codebase for multiple operating systems, but pay for this with a stack of abstraction layers—application code, third-party packages, framework runtime, platform-specific bridges, and the underlying operating system or device. When a defect manifests at this stack’s surface, fault localization is hard precisely because each layer is a plausible suspect. We argue that agent-generated native reference implementations—small vertical prototypes built directly against the platform’s native APIs with the help of coding agents—make differential, layer-bisection debugging an economically viable default tactic in cross-platform development. The contribution of this position paper is threefold: a layered fault model that makes the localization problem explicit, the proposal of native probes on demand as a concrete debugging mechanism enabled by agentic code generation, and a discussion of the conditions under which the mechanism fails (cross-layer interactions, timing-dependent behavior, probe drift) together with a research agenda for controlled empirical evaluation. The position is that agent-assisted native probes shift the cost balance of cross-platform debugging in a way that is qualitatively new: a tactic that was previously reserved for teams with full multi-platform expertise becomes available, on demand, to single-stack developers.