iOS Interview - ARC in iOS vs Garbage Collection in Android

May 24, 20244 min read#swift, #ios, #interview

I have just got this question in a job interview recently: Compare memory management mechanisms between Android and iOS. I know the differences but I couldn’t really answer the question very well due to various reasons.

Both iOS and Android have their own approaches to handling memory allocation and deallocation. And it’s useful to understand the differences between Automatic Reference Counting (ARC) in iOS and Garbage Collection in Android.

Disclaimer: The post is originally written by Claude Opus LLM from Anthropic. I have checked and rewritten some parts of it. The main purpose of the post is to help myself to answer the question better next time if I encouter this question again.

Automatic Reference Counting (ARC) in iOS

iOS uses a memory management technique called Automatic Reference Counting (ARC). ARC is a compile-time feature that automatically manages the lifetime of objects in Objective-C and Swift.

Here’s how ARC works:

  • When an object is created, ARC allocates memory for it and sets its reference count to 1.
  • When another object or variable holds a strong reference to the object, ARC increments the reference count.
  • When a strong reference is removed or goes out of scope, ARC decrements the reference count.
  • When the reference count reaches 0, ARC deallocates the object’s memory.

ARC eliminates the need for manual memory management, reducing the chances of memory leaks and making the code more readable and maintainable. However, developers still need to be mindful of retain cycles, where objects hold strong references to each other, preventing deallocation.

Garbage Collection in Android

Android, on the other hand, relies on a garbage collector to manage memory. The garbage collector is a runtime component that automatically identifies and frees up memory that is no longer being used by the application.

Here’s how garbage collection works in Android:

  • The garbage collector periodically scans the memory heap to identify objects that are no longer reachable from the application’s root set (e.g., static variables, thread stacks).
  • It marks the reachable objects and considers the unmarked objects as garbage.
  • The garbage collector then frees up the memory occupied by the garbage objects, making it available for future allocations.

Garbage collection in Android is a concurrent process, meaning it runs alongside the application threads. This helps minimize the impact on application performance. However, garbage collection can still introduce brief pauses in the application, especially when dealing with large heaps.

Key Differences

  1. Timing: ARC operates at compile-time, while garbage collection in Android happens at runtime.
  2. Determinism: ARC provides deterministic memory management, as objects are deallocated as soon as their reference count reaches 0. Garbage collection, on the other hand, is non-deterministic, as the timing of memory deallocation depends on the garbage collector’s algorithm and heuristics.
  3. Performance: ARC has a lower runtime overhead compared to garbage collection, as it doesn’t require additional threads or background processes. However, garbage collection can handle more complex memory scenarios and cycles more effectively.
  4. Developer Involvement: With ARC, developers need to be aware of memory management principles and avoid retain cycles. In Android, developers have less direct control over memory management, relying on the garbage collector to handle it automatically.


Both iOS and Android have their own approaches to memory management. ARC in iOS provides a deterministic and efficient way to manage object lifetimes, while garbage collection in Android offers automatic memory reclamation at runtime. Understanding these differences is essential for developers working on cross-platform mobile applications or transitioning between the two platforms.

Regardless of the memory management technique used, it’s crucial for developers to write memory-efficient code, profile their applications for memory usage, and optimize accordingly to ensure the best user experience.

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