Data Structure Optimizer

Data Structure Optimizer

Prerequisites & Dependencies

• Comfortable with algorithm analysis (Big O notation)
• Language runtime: Node.js 18+, Python 3.10+, or Go 1.21+
• Optional: npm i sortedmap / pip install rbtree / go data structures for experimentation

Execution Steps

1. Profile the target function/section with console.time, Python timeit, or Go benchstat to record current Big O behavior
2. Identify the bottleneck: nested loops, linear searches, frequent object allocations
3. Replace the incumbent structure with a more optimal one:
   • Array → Hash Map for O(1) lookups
   • List → Heap for priority-order processing
   • Linear Scan → Trie for prefix-heavy string sets
4. Rewrite the logic to use the new structure, keeping API compatibility
5. Re-benchmark and confirm the complexity class improved (e.g., O(n) → O(log n) or O(1))

# From O(n) list lookup to O(1) hash map
# Before: linear search
def find_user(users, target_id):
    for u in users:
        if u['id'] == target_id:
            return u
    return None

# After: hash map lookup
user_map = {u['id']: u for u in users}
def find_user_fast(user_map, target_id):
    return user_map.get(target_id)