Counting sort is good when keys are integers in a small range 0..k. It runs in O(n + k) by counting occurrences and building the output, and it can be stable (useful as a building block for radix sort).
Advanced answer
Deep dive
Expanding on the short answer — what usually matters in practice:
Complexity: compare typical operations (average vs worst-case).
Invariants: what must always hold for correctness.
When the choice is wrong: production symptoms (latency, GC, cache misses).
Explain the "why", not just the "what" (intuition + consequences).
Trade-offs: what you gain/lose (time, memory, complexity, risk).
Edge cases: empty inputs, large inputs, invalid inputs, concurrency.
Examples
A tiny example (an explanation template):
// Example: discuss trade-offs for "counting-sort:-when-can-it-be-faster-than-o(n-lo"
function explain() {
// Start from the core idea:
// Counting sort is good when keys are integers in a small range 0..k. It runs in O(n + k) by
}
Common pitfalls
Too generic: no concrete trade-offs or examples.
Mixing average-case and worst-case (e.g., complexity).