Time Complexity Analysis

Each iteration processes all $E$ edges. You run $n-1$ iterations. Total: $O(VE)$. In dense graphs where $E \approx V^2$, this becomes $O(V^3)$. Dijkstra with a binary heap runs in $O((V + E) \log V)$, which is faster when edges are non-negative. For sparse graphs where $E \approx V$, Dijkstra is $O(V \log V)$ while Bellman-Ford is $O(V^2)$.

Bellman-Ford trades speed for correctness with negative weights. Use it only when necessary. If all weights are non-negative, Dijkstra is always the better choice.

Space complexity is $O(V)$ for the data structures used.