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Project: Memory Allocator

Implement a custom memory allocator that replaces the system malloc. This is the ultimate C project — you will understand exactly how dynamic memory works at the lowest level. Every time you call malloc(64) in any C program, an allocator must decide: which chunk of memory to hand back, how to track what is free and what is not, and how to do this fast enough that it does not become a bottleneck. Real-world allocators like glibc’s ptmalloc, Google’s tcmalloc, and Facebook’s jemalloc are engineering marvels that balance speed, fragmentation, thread scalability, and cache behavior. In this project, you will build a simplified version from scratch to understand the fundamental design decisions they all share.

Allocator Design

Think of the allocator as managing a parking lot. Cars (allocations) come and go at unpredictable times, leaving gaps of various sizes. The manager must decide where to park each new car (allocation strategy), when to re-stripe the lot to consolidate empty spaces (coalescing), and how to handle rush hour without creating a traffic jam (thread safety).
1

System Interface

Get raw memory pages from the kernel with sbrk (extend the data segment) or mmap (request a new memory region). This is like acquiring land for the parking lot — you ask the OS for a plot.
2

Block Management

Track which regions are free and which are allocated using metadata headers. Each block carries a small header that records its size, status, and links to neighboring blocks.
3

Fragmentation

Handle splitting (cutting a large block to satisfy a smaller request) and coalescing (merging adjacent free blocks back together). Without coalescing, your heap becomes Swiss cheese — lots of small holes, none big enough to use.
4

Performance

Optimize for speed and memory efficiency. First-fit is simple but slow for large heaps. Segregated free lists give O(1) allocation for common sizes — the same approach used by glibc’s ptmalloc and tcmalloc.

Block Structure


Basic Implementation


Advanced: Best-Fit and Segregated Lists

The basic allocator scans a single linked list to find a free block. With thousands of blocks, this becomes painfully slow (O(n) per allocation). Segregated free lists solve this by maintaining separate lists for different size ranges — like a hardware store with separate bins for screws, bolts, and washers instead of one giant pile. When a 32-byte request arrives, you only search the 32-byte bin, which is typically very short. This is the core idea behind glibc’s ptmalloc: small allocations go to “fastbins” (singly-linked, no coalescing), medium ones go to “smallbins” (doubly-linked, sorted), and large ones go to “largebins” (sorted by size with skip lists). Our simplified version captures the key insight without all the production complexity.

Interposition: Replace System malloc

One of the most powerful testing techniques in systems programming: you can replace the system malloc with your own implementation without recompiling the target program. Linux’s dynamic linker resolves symbols at load time, and LD_PRELOAD forces it to look in your library first. This is the same mechanism that tools like Valgrind, Electric Fence, and tcmalloc use to inject themselves.
Pitfall: Your allocator must handle the bootstrapping problem. Some libc functions called during startup (like dlsym or printf) may themselves call malloc. If your allocator is not ready yet, you get an infinite recursion. Production interposition libraries use a small static bootstrap buffer for early allocations.

Testing


Performance Benchmarks


Debugging Features


Common Pitfalls

Alignment bugs: Returning unaligned pointers causes SIGBUS on some architectures and silent performance degradation on x86. Always round allocation sizes up to the alignment boundary (typically 16 bytes on 64-bit systems). If your test suite passes but benchmarks show unexpectedly slow performance, check alignment first.Forgetting to coalesce: Without coalescing, your allocator suffers from “external fragmentation” — plenty of total free memory, but no single block large enough for a request. After 10,000 allocation/free cycles, a non-coalescing allocator can waste 50%+ of heap space.Thread safety oversights: The most common bug is forgetting to hold the lock during coalescing or splitting. Both operations modify multiple blocks’ pointers, and a concurrent allocation that sees a half-updated linked list will corrupt the heap.sbrk is not thread-safe: On older Linux kernels, sbrk is not safe to call from multiple threads. Prefer mmap for new allocations in threaded programs, or protect sbrk calls with the global lock (as our implementation does).Header corruption goes undetected: Without the magic number check, a buffer overflow in user code can silently overwrite a block header, causing the allocator to follow corrupted linked list pointers on the next free. This produces crashes that look completely unrelated to the actual bug. The magic canary catches this early.

Learning Outcomes

  • How heap memory actually works at the system call level
  • Block headers, metadata overhead, and alignment requirements
  • Memory fragmentation (internal vs external) and coalescing strategies
  • Multiple allocation strategies (first-fit, best-fit, segregated lists)
  • Thread-safe allocator design and the performance cost of global locks
  • System calls: sbrk for contiguous growth, mmap for large/independent regions
  • Performance measurement and the real cost of malloc in tight loops
  • Memory debugging, leak detection, and corruption canaries

Extensions

Arena Allocator

Fast bump allocation with bulk free

Pool Allocator

Fixed-size allocations for objects

Thread-Local Caching

Per-thread free lists like tcmalloc

Memory Pools

Pre-allocated pools for game engines

Next Up

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