How WebAssembly Handles Memory and Garbage Collection

WebAssembly (Wasm) utilizes a secure, low-level memory model that has recently evolved to support high-level programming languages more efficiently. Historically, WebAssembly relied solely on a contiguous, flat range of bytes called linear memory, which required manual management. However, the introduction of the WebAssembly Garbage Collection (WasmGC) extension has changed this landscape, allowing Wasm to directly interface with the host environment’s garbage collector. This article explores how Wasm manages linear memory, how it handles manual allocation, and how WasmGC enables automatic memory management for languages like Kotlin, Dart, and Java.

WebAssembly Linear Memory

At its core, WebAssembly operates using a sandboxed memory model known as linear memory. Linear memory is represented as a contiguous array of raw bytes that can be dynamically expanded in 64 KiB increments (called pages).

When compiling low-level languages like C, C++, or Rust to WebAssembly, the compiled code treats this linear memory as its physical RAM. Security is a primary benefit of this design: a Wasm module can only access its own allocated linear memory space. It cannot access memory addresses outside of this sandbox, preventing common vulnerabilities like buffer overflows from affecting the host system.

Manual Memory Management in Wasm

Because linear memory is just a raw byte array, WebAssembly itself has no built-in understanding of complex data structures like objects, trees, or graphs. For languages that do not have garbage collection (e.g., C/C++ and Rust), memory management must be handled manually within the compiled module:

1. Allocators: The compiled Wasm binary includes a software allocator (such as dlmalloc or wee_alloc) packaged directly inside the module.
2. Allocation & Deallocation: When the application runs, the allocator manages the linear memory by assigning specific byte offsets to variables and structures. Developers use standard manual allocation patterns (like malloc and free in C, or Rust’s ownership system) to manage the lifecycle of these bytes.
3. Host Interaction: If the host environment (such as a web browser running JavaScript) needs to access data within Wasm’s linear memory, it must read or write directly to the buffer using typed arrays.

The Challenge of Managed Languages

For high-level, garbage-collected languages like Java, C#, Go, and Dart, compiling to traditional WebAssembly linear memory presented significant challenges.

To run these languages, developers had to compile the language’s entire runtime—including its custom garbage collector—into the Wasm binary. This resulted in bloated file sizes, slow load times, and poor performance, as the internal GC had to run on top of Wasm’s linear memory without understanding the host browser’s optimization cycles.

Introducing WebAssembly Garbage Collection (WasmGC)

To solve the limitations of managed languages, the WebAssembly community developed WasmGC, which is now a standard feature in major web browsers.

WasmGC integrates garbage collection directly into the WebAssembly runtime by defining new, high-level types (such as structs and arrays) directly in the Wasm bytecode. Instead of managing raw bytes in linear memory, WasmGC allows compilers to generate instructions that allocate garbage-collected objects.

How WasmGC Works

WasmGC bridges the gap between WebAssembly and the host virtual machine (such as the browser’s JavaScript engine) through the following mechanisms:

• Host-VM Integration: Instead of shipping a custom garbage collector inside the Wasm file, WasmGC leverages the highly optimized garbage collector already built into the host engine (e.g., V8 in Chrome, SpiderMonkey in Firefox).
• Reference Types: WasmGC introduces managed reference types. Wasm can hold references to host-managed objects, allowing the host’s garbage collector to track references, detect cycles, and safely reclaim memory when objects are no longer needed.
• Performance Benefits: By offloading GC to the host, Wasm binaries for managed languages are significantly smaller, download faster, and benefit from the host engine’s advanced garbage collection optimizations (like generational collection and concurrent sweeping).