Execution, Memory, and Advanced Garbage Collection Concepts

Why Memory Management Defines System Performance

Every program interacts with memory, whether explicitly (C, C++) or through a runtime system (Java, Go) . The method of memory management determines performance, stability, and scalability . In real-time systems — such as automated trading, medical monitoring, and networking —a delay in memory management can lead to dropped packets, failed trades, or system crashes .

Manual Memory Management vs. Garbage Collection

In languages like C and C++ , memory management is manual —meaning the programmer must allocate ( malloc , new ) and free ( free , delete ) memory.

1#include <stdio.h>
2#include <stdlib.h>
3
4void memory_leak() {
5    int* ptr = (int*)malloc(4 * sizeof(int)); // Allocated but never freed
6}
7
8void use_after_free() {
9    int* ptr = (int*)malloc(sizeof(int));
10    free(ptr);
11    *ptr = 42;  // ERROR: Use after free!
12}
13
14int main() {
15    memory_leak();
16    use_after_free();
17    return 0;
18}

How Garbage Collection Works: Tracing, Sweeping, and Thresholds

Instead of manually freeing memory, garbage collection (GC) automatically tracks and removes unreachable objects . GC does not run continuously but is triggered when:

• Heap Pressure (≥ 70% memory usage): When heap utilization exceeds a threshold, a collection is triggered.
• Trigger Points (e.g., object count ≥ 100k): Some GC implementations trigger sweeps after a specific object count.
• Background Sweeps (every 200ms in some VMs): Some environments periodically perform minor garbage collections in the background.

Memory Pooling & Slab Allocation: Reducing Fragmentation

Memory pooling preallocates memory in chunks, reducing fragmentation and improving allocation speed. A deeper optimization involves slab allocation , where memory is divided into fixed-size blocks.

1#include <stdio.h>
2#include <stdlib.h>
3
4#define BLOCK_SIZE 64
5#define NUM_BLOCKS 16
6
7char slab_pool[BLOCK_SIZE * NUM_BLOCKS];
8char* free_list[NUM_BLOCKS];
9
10void init_pool() {
11    for (int i = 0; i < NUM_BLOCKS; i++)
12        free_list[i] = &slab_pool[i * BLOCK_SIZE];
13}
14
15void* slab_alloc() {
16    for (int i = 0; i < NUM_BLOCKS; i++) {
17        if (free_list[i]) {
18            char* block = free_list[i];
19            free_list[i] = NULL;  // Mark as used
20            return block;
21        }
22    }
23    return NULL;  // Out of memory
24}
25
26void slab_free(void* ptr) {
27    for (int i = 0; i < NUM_BLOCKS; i++) {
28        if (&slab_pool[i * BLOCK_SIZE] == ptr) {
29            free_list[i] = ptr;  // Mark as free
30            break;
31        }
32    }
33}
34
35int main() {
36    init_pool();
37    void* mem = slab_alloc();
38    printf("Allocated block at %p\n", mem);
39    slab_free(mem);
40    return 0;
41}

This method reduces fragmentation and ensures constant-time allocations , making it ideal for high-performance systems .

Memory Management Trade-offs Matter

Understanding garbage collection, memory fragmentation, and manual allocation helps optimize performance-critical applications . The right memory model depends on the trade-offs between automation, control, and efficiency .