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LeakCanary ObjectWatcher Deep Dive — How Android Leak Detection Starts Understand how ObjectWatcher uses weak references, reference queues, and retained-object checks to power LeakCanary’s memory leak detection flow. In the previous article, we looked at why memory leaks matter and how LeakCanary detects them at a high level. This time, we are going one layer deeper into the internal component that quietly powers the first stage of leak detection: ObjectWatcher . If you want to understand LeakCanary beyond setup snippets and notifications, ObjectWatcher is the right place to start. Table of Contents 1. What Is ObjectWatcher? 2. Why ObjectWatcher Matters 3. How ObjectWatcher Works Internally 4. Watching Destroyed Objects 5. Weak References and ReferenceQueue 6. How Retained Objects Are Detected 7. Manual Watching for Custom Objects 8. Why This Matters for Senior Android Engineers 9. Analyze ...

Why Android Memory Leaks Still Matter — and How LeakCanary Helps You Detect Them Early A practical introduction to Android memory leaks, LeakCanary, Shark, heap dumps, and modern leak analysis workflows. Every Android engineer has faced the dreaded OutOfMemoryError . It usually does not happen on day one, but weeks after release, when users have navigated through multiple screens, opened heavy flows, and stressed the app in ways test devices never fully did. The silent culprit is often a memory leak. In this guide, we will look at why Android memory leaks happen, why they are dangerous, how LeakCanary detects them, and how this series will help you understand the internals behind LeakCanary and Shark. Table of Contents 1. What Is a Memory Leak in Android? 2. Why Memory Leaks Are Dangerous 3. LeakCanary for Android Memory Leak Detection 4. How LeakCanary Works 5. Why This Series Matters 6. Analyze...

LeakCanary Internals: The Complete Guide for Android Engineers A canonical guide to Android memory leak debugging with LeakCanary, ObjectWatcher, heap dumps, Shark, retained size, CI/CD, reporting, and modern prevention workflows. Memory leaks are one of the most deceptive classes of Android bugs. They rarely fail fast, they often hide behind otherwise “working” features, and they slowly degrade user experience through extra garbage collection, UI jank, battery drain, and eventual crashes. The danger is not just that memory is retained — it is that the cost compounds quietly until the app becomes unstable. That is why LeakCanary remains one of the most important tools in Android performance engineering. But to use it well, it is not enough to treat it like a black-box library that throws notifications. The real leverage comes from understanding how it works internally: how objects are watched, when heap dumps are triggered, how Shark reconstr...

  Your SDK has 12 transitive dependencies. Your consumer’s build.gradle shouldn’t know about any of them. Why This Problem Is Uniquely Hard in KMP If you’re building a Kotlin Multiplatform SDK, you’re already dealing with complexity that traditional Android libraries never face. Your commonMain code compiles to both JVM bytecode (Android) and native binaries (iOS). On iOS, the XCFramework is self-contained - all Kotlin/Native dependencies compile into a single static binary. There's no "dependency resolution" on the Swift side. But on Android? You’re back in Gradle-land. Your KMP module produces a standard .aar , and every api() or implementation() dependency in your build.gradle.kts becomes a transitive edge in the consumer's dependency graph. The irony: the platform with the better tooling has the worse distribution story. This asymmetry is what makes Fat AAR essential for KMP SDK teams. iOS gets zero-config by default (static XCFramework). Android needs us to b...