Both are divide‑and‑conquer sorts. QuickSort partitions around a pivot, is in‑place and very fast on average O(n log n), but has O(n²) worst‑case and is not stable. MergeSort splits and merges, is stable with guaranteed O(n log n) worst‑case, but needs O(n) extra memory and works well for linked lists/external sorting.
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 "quicksort-vs-mergesort?"
function explain() {
// Start from the core idea:
// MergeSort is stable with O(n log n) worst-case. QuickSort is unstable, often faster in pra
}
Common pitfalls
Too generic: no concrete trade-offs or examples.
Mixing average-case and worst-case (e.g., complexity).