Architectural Invariant Design: KMP Wasm-GC Cross-Runtime Reference Lifetime Synchronization
KMP Wasm-GC Cross-Runtime Reference Lifetime Synchronization defines an industrial-grade behavioral standard for mobile engineering. Eliminates cross-runtime frame drops and native bridge leaks by deterministically synchronizing Kotlin Multiplatform Wasm-GC allocations with host UI event cycles. Replaces non-deterministic finalizers with strict disposable handles and scoped host reference registries across the execution boundary. Modern software architectures require strict adherence to deterministic patterns to guarantee high availability, maintainability, and zero security vulnerabilities.
Hazard Analysis: What Breaks Without This Rule
The following failure modes have been cataloged from hundreds of hours of production code reviews where AI assistants produced non-compliant implementations:
| Failure Mode | AI Symptom (The Anti-Pattern) | Severity | Production Impact & Remedy |
|---|---|---|---|
| AI Hallucination & Deprecation Drift | Implicit Cross-Runtime Retain Cycles Relying on Host GC Finalizers Leading to Dual-Heap Fragmentation and Frame Drops | Critical | Violating this industrial standard introduces regression bugs, security risks, and unexpected runtime failures in production. Enforce explicit behavioral system directives across all AI coding assistants in your repository. |
| Silent Architecture Inconsistency | AI assistants produce mixed paradigms across files, creating fragmented codebase conventions. | Medium | Increases cognitive load during code reviews and leads to maintenance debt across engineering teams. Pin project conventions in .cursor/rules, CLAUDE.md, and AGENTS.md so all team agents follow identical guardrails. |
Step-by-Step Production Directives
Each rule constraint below is injected into the AI agent's system prompt to establish deterministic boundaries:
Engineers MUST ALWAYS wrap exported Wasm-GC delegates passed across the host boundary in explicit AutoCloseable or DisposableHandle abstractions.
Engineers MUST ALWAYS wrap exported Wasm-GC delegates passed across the host boundary in explicit AutoCloseable or DisposableHandle abstractions.
Engineers MUST NOT rely on host garbage collection or FinalizationRegistry to schedule the disposal of Wasm-GC references tied to native/DOM rendering loops.
Engineers MUST NOT rely on host garbage collection or FinalizationRegistry to schedule the disposal of Wasm-GC references tied to native/DOM rendering loops.
Code SHOULD pass opaque integer handles or raw scalar IDs across the interop boundary instead of retaining dynamic Kotlin closures in host UI listeners.
Code SHOULD pass opaque integer handles or raw scalar IDs across the interop boundary instead of retaining dynamic Kotlin closures in host UI listeners.
Services MUST clear bidirectional interop bridges synchronously within the UI component unmount or disposal phase (e.g., via Compose Multiplatform DisposableEffect).
Services MUST clear bidirectional interop bridges synchronously within the UI component unmount or disposal phase (e.g., via Compose Multiplatform DisposableEffect).
Components NEVER construct circular references where a host DOM/platform node retains a Kotlin exported lambda that simultaneously captures the host node via closure.
Components NEVER construct circular references where a host DOM/platform node retains a Kotlin exported lambda that simultaneously captures the host node via closure.
Frequently Asked Technical Questions
Common questions developers face when configuring AI coding assistants for this stack:
Q:Why is KMP Wasm-GC Cross-Runtime Reference Lifetime Synchronization critical for AI coding assistants?
Eliminates cross-runtime frame drops and native bridge leaks by deterministically synchronizing Kotlin Multiplatform Wasm-GC allocations with host UI event cycles. Replaces non-deterministic finalizers with strict disposable handles and scoped host reference registries across the execution boundary. Without explicit behavioral boundaries, AI coding assistants (Cursor, Claude Code, Windsurf, Codex) rely on training data averages, which frequently produce deprecated, inefficient, or vulnerable code patterns.
Q:How does adopting this rule prevent AI hallucinations?
This rule explicitly declares what the AI must avoid (Implicit Cross-Runtime Retain Cycles Relying on Host GC Finalizers Leading to Dual-Heap Fragmentation and Frame Drops) and prescribes verified positive examples. Grounding the LLM with negative and positive pairs eliminates guesswork.
Q:Which AI coding environments are supported?
This specification is multi-platform compatible: Cursor (.cursor/rules/*.mdc & .cursorrules), Anthropic Claude Code (CLAUDE.md), Windsurf (.windsurfrules), Codex / Cline (AGENTS.md), and GitHub Copilot (.github/copilot-instructions.md).
Q:Can I combine this rule with other technology stacks?
Yes. Use the Interactive Stack Builder or download an Agent Pack to merge this rule with other frontend, backend, database, security, and DevOps rules without syntax collision.