Manual Memory Management vs. ARC for Cross-Platform Object Lifecycles

Answer the question first

For long‑term maintainability, a single ARC‑style reference‑counting wrapper on desktop is the more sustainable choice. It keeps the shared codebase free of platform‑specific Free/Dispose logic, reduces the risk of mismatched cleanup, and aligns the desktop lifecycle model with the mobile ARC model. The trade‑off is a modest runtime overhead that must be measured against the application’s allocation profile.

Why the wrapper is preferable

• **Unified API** – All objects expose Retain and Release, so the same code compiles for Windows, macOS, iOS, and Android.
• **Deterministic cleanup** – Desktop objects still receive Release calls in try..finally blocks, preserving deterministic destruction while avoiding manual Free calls.
• **Reduced conditional compilation** – Only the wrapper’s implementation differs per platform; the rest of the code remains identical.
• **Easier refactoring** – When a new platform is added, the wrapper can be extended instead of adding new {$IFDEF} branches.

Performance considerations

• Reference counting adds a small atomic increment/decrement per allocation. For most UI applications this is negligible, but for high‑frequency object churn (e.g., particle systems) the overhead can become noticeable.
• Atomic operations may serialize across threads, introducing contention. Profiling is required to quantify this impact.
• Memory usage increases by the size of the reference counter (typically 4–8 bytes) per object.

Recommended implementation steps

1. Define a generic TRefCounted base class that implements Retain and Release using AtomicIncrement/AtomicDecrement.
2. Derive all shared objects from TRefCounted and replace every Free with Release inside try..finally.
3. On mobile, keep the existing ARC semantics and use Weak references to break cycles.
4. Write a small unit test that allocates and releases a large number of objects to verify that no leaks occur on both desktop and mobile builds.
5. Run a performance benchmark (e.g., 10 000 objects per frame) on Windows/macOS to measure the per‑object overhead and decide if the wrapper is acceptable for your workload.
6. If the overhead is too high for a specific module, consider a hybrid approach: keep a manual Free path for that module while the rest of the code uses the wrapper.

What to verify

• Static analysis shows no remaining Free calls in the shared code when the wrapper is enabled.
• Leak detection tools (Valgrind on Windows, Instruments on macOS) confirm zero leaks.
• Multithreaded profiling indicates acceptable contention on reference counter operations.

Missing diagnostic detail

To decide whether the wrapper overhead is acceptable, I need the typical allocation frequency for desktop targets (objects per second). Please provide that figure so the benchmark can be tailored to your workload.