Floyd–Warshall computes shortest paths between all pairs of vertices. It runs in O(V^3) time and uses O(V^2) memory, so it’s practical mainly for smaller or dense graphs. It can handle negative edges, but not negative cycles.
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 "what-does-the-floyd–warshall-algorithm-compute-a"
function explain() {
// Start from the core idea:
// Floyd–Warshall computes shortest paths between all pairs of vertices. It runs in O(V^3) ti
}
Common pitfalls
Too generic: no concrete trade-offs or examples.
Mixing average-case and worst-case (e.g., complexity).