Kruskal sorts edges and adds the smallest ones that don’t create cycles (uses Union-Find). Prim grows a tree from a start node using a priority queue of edges. Both can be O(E log E) / O(E log V) depending on implementation.
Advanced answer
Deep dive
Expanding on the short answer — what usually matters in practice:
Context (tags): mst, kruskal, prim, graphs, big-o
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 "kruskal-vs-prim-for-mst-—-how-do-they-differ?"
function explain() {
// Start from the core idea:
// Kruskal sorts edges and adds the smallest ones that don’t create cycles (uses Union-Find).
}
Common pitfalls
Too generic: no concrete trade-offs or examples.
Mixing average-case and worst-case (e.g., complexity).