Global edge connectivity
Given a connected undirected graph with n nodes (0..n-1) and edges [u, v] (each edge has unit capacity; parallel edges increase capacity), return its global edge connectivity: the minimum number of edges whose removal disconnects the graph (equivalently the global minimum cut). For n <= 1 return 0. Use max-flow/min-cut: fix one node and take the min over all other nodes of the s-t max flow. Assume 1 <= n <= 60 so repeated unit-capacity max-flow finishes under 5s.
Implement
edge_connectivity(n: int, edges: list[list[int]]) → intExamples
in
[4,[[0,1],[1,2],[2,3],[3,0]]]out2What a strong answer looks like
State your approach and its time/space complexity out loud before you optimize. Handle the edge cases (empty input, duplicates, overflow), and say why you chose this over the brute force. Green tests are the floor, not the grade.
0:00 of about 40 min
solution.py
InputExpectedGot
[4,[[0,1],[1,2],[2,3],[3,0]]]2not run yetsample