Lottery-Tracker/SKILLS/25-algorithms-performance.md

Algorithms & Performance

Use this skill when performance matters (large inputs, hot paths, or repeated calls).

Checklist

• Identify the state you’re recomputing.
• Add memoization / caching when the same subproblem repeats.
• Prefer linear scans + caches over nested loops when possible.
• If you can write it as a recurrence, you can test it.

Practical heuristics

• Measure first when possible (timing + input sizes).
• Optimize the biggest wins: avoid repeated I/O, repeated parsing, repeated network calls.
• Keep caches bounded (size/TTL) and invalidate safely.
• Choose data structures intentionally: dict/set for membership, heap for top-k, deque for queues.

Review notes (for PRs)

• Call out accidental O(n²) patterns.
• Suggest table/DP or memoization when repeated work is obvious.
• Add tests that cover base cases + typical cases + worst-case size.