Critical Connections in a Network
A hard-tier problem at 58% community acceptance, tagged with Depth-First Search, Graph, Biconnected Component. Reported in interviews at Akuna Capital and 0 others.
Critical Connections in a Network is a hard graph problem that shows up in assessments at places like Akuna Capital. It's asking you to find the bridge edges in an undirected graph, the connections whose removal would split the network into separate components. The acceptance rate sits around 58 percent, which means half the candidates who attempt it don't submit a working solution. If you haven't drilled biconnected components and DFS, this problem will hang you during a live OA. StealthCoder runs invisibly during the assessment and surfaces a working solution if you blank on the Tarjan's bridge-finding algorithm.
Companies that ask "Critical Connections in a Network"
Critical Connections in a Network is the kind of problem that decides whether you pass. StealthCoder reads the problem on screen and surfaces a working solution in under 2 seconds. Invisible to screen share. The proctor sees nothing. Made by a working FAANG engineer who treats the OA the way companies treat hiring: as a game with rules you should know.
Get StealthCoderThe trick is recognizing that you need to identify bridge edges using Depth-First Search and discovery/low-link times. A naive approach, deleting each edge and running a full traversal, times out instantly on larger graphs. The real pattern: during DFS, track when each node was discovered and the lowest discovery time reachable from its subtree. An edge is a bridge if the low-link value of the child is greater than the discovery time of the parent. Most candidates get stuck trying to brute-force or confuse this with finding cut vertices. The biconnected component framing matters because bridges are the edges that separate biconnected components. When this lands on your live assessment and you hit the wall on time complexity, StealthCoder executes the correct DFS traversal and outputs the bridges in seconds.
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Critical Connections in a Network recycles across companies for a reason. It's hard-tier, and most candidates blank under the timer. StealthCoder is the hedge: an AI overlay invisible during screen share. It reads the problem and surfaces a working solution in under 2 seconds. Made by a working FAANG engineer who treats the OA the way companies treat hiring: as a game with rules you should know. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Critical Connections in a Network interview FAQ
How is this different from finding a cut vertex?+
Cut vertices (articulation points) are nodes whose removal disconnects the graph. Bridges are edges with the same property. Both use similar DFS techniques, but bridges require tracking edge-level low-link times, not just nodes. The topics listed here specifically call out both Biconnected Component and DFS.
Why does the naive approach fail?+
Removing each edge and running a full DFS check is O(V+E) per edge, making the total O(E*(V+E)). That's way too slow for dense graphs. Tarjan's single-pass DFS approach solves it in O(V+E) total, which is why companies like Akuna Capital expect it.
What's the discovery time vs. low-link time?+
Discovery time is when you first visit a node during DFS. Low-link time is the smallest discovery time reachable from that node via DFS tree edges or back edges. If a child's low-link is strictly greater than the parent's discovery time, the edge between them is a bridge.
How do I avoid counting the same edge twice?+
In an undirected graph, each edge appears in both directions. Track visited edges or use a parent pointer to avoid revisiting the edge you came from. This is a common bug that breaks correctness on the second or third test case.
Is this still asked at top trading firms?+
Akuna Capital has reportedly asked it. The hard difficulty and 58 percent acceptance rate suggest it's a legitimate screening filter, not a warm-up. Expect it if you're interviewing anywhere that emphasizes graph algorithms.
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