KMP Native 2.1 Concurrent Cleaner and Finalizer Non-Blocking Invariant

--- description: KMP Native 2.1 Concurrent Cleaner and Finalizer Non-Blocking Invariant - Enforces strict non-blocking execution inside Kotlin/Native Cleaner and finalization routines in Kotlin Multiplatform 2.1+. Prohibits synchronized mutex acquisition, coroutine runBlocking, and synchronous I/O within native garbage collection worker threads to eliminate runtime deadlocks and collector starvation. globs: **/*.kt, **/nativeMain/**/*.kt, **/iosMain/**/*.kt, **/posixMain/**/*.kt alwaysApply: true verified_by: "agentrules.org" license: "CC-BY-4.0" source: "https://agentrules.org/rules/kmp-native-gc-concurrency-finalizer-invariant" --- # KMP Native 2.1 Concurrent Cleaner and Finalizer Non-Blocking Invariant > **Severity**: CRITICAL | **Category**: mobile > **Anti-Pattern Warning**: Executing blocking operations or mutex synchronizations inside Kotlin/Native createCleaner blocks ## System Constraints You are a Principal Software Architect enforcing Kotlin Multiplatform 2.1 Native GC Concurrency Finalizer Invariants. You must ensure that native finalization hooks, cleaners, and deallocation blocks never block the GC thread pool. Mandate lock-free, asynchronous, and non-blocking teardown patterns. ## Strict Guidelines - Engineers MUST ALWAYS isolate native resource cleanup arguments into separate, non-referential state objects when invoking createCleaner to prevent retaining circular references. - Engineers MUST NOT invoke runBlocking, CountDownLatch.await, pthread_mutex_lock, or synchronous file/network I/O inside a createCleaner action lambda. - Code SHOULD utilize lock-free atomic releases or native platform deallocators (e.g., platform.posix.free, CFRelease) directly within cleaners. - Services MUST dispatch complex teardown logic that requires synchronization or asynchronous work to a dedicated background CoroutineScope rather than awaiting completion on the GC finalizer thread. - Components NEVER capture the outer class instance inside createCleaner; doing so indefinitely resurrects the object and leaks native heap memory. ## Bad vs Good Implementations ### Native Resource Deallocation via createCleaner #### Bad Antipattern (AI Common Hallucination) > **Why it fails**: Capturing 'this' prevents the object from ever being collected. Executing runBlocking and waiting on a coroutine Mutex inside the cleaner thread blocks the concurrent GC worker, causing deadlocks if another thread holding the mutex triggers garbage collection. ```kotlin import kotlin.native.internal.createCleaner import kotlinx.coroutines.runBlocking import kotlinx.coroutines.sync.Mutex import platform.posix.free import kotlinx.cinterop.CPointer class NativeSqliteBridge(private val dbPointer: CPointer<*>) { private val mutex = Mutex() // ANTI-PATTERN: Captures 'this' reference and performs blocking synchronization inside cleaner @OptIn(ExperimentalStdlibApi::class) private val cleaner = createCleaner(this) { runBlocking { mutex.lock() // DEADLOCK: GC worker thread blocked awaiting application mutex try { free(it.dbPointer) } finally { mutex.unlock() } } } } ``` #### Production Standard (Correct) > **Standard**: The cleanup action captures only the isolated NativeResourceState object, breaking circular reference chains. The cleaner executes pure non-blocking C runtime free(), avoiding GC thread starvation and mutex inversions. ```kotlin import kotlin.native.internal.createCleaner import platform.posix.free import kotlinx.cinterop.CPointer import kotlinx.cinterop.NativePtr // Safe state holder holding ONLY unmanaged primitive references private class NativeResourceState(val rawPointer: CPointer<*>?) class NativeSqliteBridge(dbPointer: CPointer<*>) { // GOOD: Disassociated raw pointer state with zero references to the host class private val state = NativeResourceState(dbPointer) @OptIn(ExperimentalStdlibApi::class) private val cleaner = createCleaner(state) { resourceState -> // INVARIANT: Strictly lock-free, non-blocking pure POSIX deallocation resourceState.rawPointer?.let { ptr -> free(ptr) } } } ```

Architectural Specification & Invariant Rationale

Architectural Invariant Design: KMP Native 2.1 Concurrent Cleaner and Finalizer Non-Blocking Invariant

KMP Native 2.1 Concurrent Cleaner and Finalizer Non-Blocking Invariant defines an industrial-grade behavioral standard for mobile engineering. Enforces strict non-blocking execution inside Kotlin/Native Cleaner and finalization routines in Kotlin Multiplatform 2.1+. Prohibits synchronized mutex acquisition, coroutine runBlocking, and synchronous I/O within native garbage collection worker threads to eliminate runtime deadlocks and collector starvation. Modern software architectures require strict adherence to deterministic patterns to guarantee high availability, maintainability, and zero security vulnerabilities.

Framework Paradigm Shift & Drift MechanicsLLMs are trained on millions of open-source repositories containing outdated code, legacy idioms, and unpatched antipatterns. When coding assistants generate implementations for this stack, they default to common statistical tokens: Executing blocking operations or mutex synchronizations inside Kotlin/Native createCleaner blocks Without an explicit system instruction file, developers spend hours debugging silent failures.

Failure Modes & Production Blast Radius

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	Executing blocking operations or mutex synchronizations inside Kotlin/Native createCleaner blocks	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.

Architectural Directives in Detail

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 isolate native resource cleanup arguments into separate, non-referential state objects when invoking createCleaner to prevent retaining circular references.

Rationale:AI models frequently generate unconstrained code here because statistical language distributions lack project-specific architectural context. Mandating this directive ensures that generated code adheres to verified industrial production requirements.