Bridges in Graph Tarjan's Algorithm in DSA C# - Time & Space Complexity

Time Complexity: Bridges in Graph Tarjan's Algorithm

O(n + m)

Understanding Time Complexity

We want to understand how the time needed to find bridges in a graph grows as the graph gets bigger.

Specifically, how does the algorithm's work increase when we add more nodes and edges?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

void DFS(int u, int parent) {
    visited[u] = true;
    disc[u] = low[u] = time++;
    foreach (int v in graph[u]) {
        if (v == parent) continue;
        if (!visited[v]) {
            DFS(v, u);
            low[u] = Math.Min(low[u], low[v]);
            if (low[v] > disc[u]) {
                // (u, v) is a bridge
            }
        } else {
            low[u] = Math.Min(low[u], disc[v]);
        }
    }
}
    

This code runs a depth-first search to find bridges by tracking discovery and low times for each node.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: DFS visits each node once and explores all its edges.
• How many times: Each node is visited once; each edge is checked twice (once from each end).

How Execution Grows With Input

As the number of nodes (n) and edges (m) grow, the algorithm visits each node and edge once or twice.

Input Size (n, m)	Approx. Operations
10 nodes, 15 edges	About 40 operations (10 nodes + 30 edge checks)
100 nodes, 200 edges	About 500 operations (100 nodes + 400 edge checks)
1000 nodes, 3000 edges	About 7000 operations (1000 nodes + 6000 edge checks)

Pattern observation: The work grows roughly in proportion to nodes plus edges.

Final Time Complexity

Time Complexity: O(n + m)

This means the time needed grows linearly with the number of nodes and edges in the graph.

Common Mistake

[X] Wrong: "The algorithm checks every possible pair of nodes, so it must be O(n²)."

[OK] Correct: The algorithm only explores edges that actually exist, not all pairs, so it depends on edges, not all pairs.

Interview Connect

Understanding this linear time complexity helps you explain how efficient graph algorithms work in real problems.

It shows you can handle large graphs without slowdowns, a key skill in many coding challenges.

Self-Check

"What if the graph was represented as an adjacency matrix instead of adjacency lists? How would the time complexity change?"

Practice

1. What is the main purpose of Tarjan's algorithm when finding bridges in a graph?

easy

A. To sort nodes in topological order

B. To find the shortest path between two nodes

C. To detect cycles in a graph

D. To find edges that, if removed, increase the number of connected components

Solution

1. Step 1: Understand what a bridge is in a graph

   A bridge is an edge that, when removed, increases the number of connected components in the graph.

2. Step 2: Identify Tarjan's algorithm goal

   Tarjan's algorithm finds such edges efficiently by using depth-first search and tracking discovery and low times.

3. Final Answer:

   To find edges that, if removed, increase the number of connected components -> Option D

4. Quick Check:

   Bridges = edges increasing components when removed [OK]

Hint: Bridges disconnect graph if removed [OK]

Common Mistakes:

• Confusing bridges with cycles
• Thinking it finds shortest paths
• Mixing bridges with articulation points

2. Which of the following is the correct way to declare the arrays used for discovery and low times in C# for Tarjan's algorithm?

easy

A. int disc = new int[n]; int low = new int[n];

B. int[] disc = new int[n]; int[] low = new int[n];

C. int disc[] = new int[n]; int low[] = new int[n];

D. int[] disc, low = new int[n];

Solution

1. Step 1: Recall C# array declaration syntax

   In C#, arrays are declared as type[] name = new type[size];

2. Step 2: Check each option

   int[] disc = new int[n]; int[] low = new int[n]; uses correct syntax for both arrays. int disc[] = new int[n]; int low[] = new int[n]; uses Java-style syntax, invalid in C#. int disc = new int[n]; int low = new int[n]; misses [] for arrays. int[] disc, low = new int[n]; declares only low as array, disc is just a variable.

3. Final Answer:

   int[] disc = new int[n]; int[] low = new int[n]; -> Option B

4. Quick Check:

   C# arrays = type[] name = new type[size] [OK]

Hint: Use type[] name = new type[size] in C# [OK]

Common Mistakes:

• Using Java array syntax in C#
• Forgetting [] in declaration
• Declaring multiple arrays incorrectly

3. Given the following graph edges and Tarjan's algorithm code snippet, what is the output list of bridges?

Edges: (0-1), (1-2), (2-0), (1-3)

// Assume graph is adjacency list
// Tarjan's algorithm finds bridges

Output bridges:

medium

A. [(0, 1)]

B. [(0, 1), (1, 3)]

C. [(1, 3)]

D. []

Solution

1. Step 1: Analyze the graph structure

   The edges (0-1), (1-2), and (2-0) form a cycle. The edge (1-3) connects node 3 to the cycle.

2. Step 2: Identify bridges

   Edges in a cycle are not bridges because removing them does not disconnect the graph. The edge (1-3) is a bridge because removing it disconnects node 3.

3. Final Answer:

   [(1, 3)] -> Option C

4. Quick Check:

   Only edge (1-3) disconnects graph [OK]

Hint: Edges in cycles are not bridges [OK]

Common Mistakes:

• Marking cycle edges as bridges
• Ignoring leaf edges as bridges
• Confusing nodes and edges

4. Identify the bug in this Tarjan's algorithm snippet for finding bridges in C#:

void DFS(int u, int parent) {
  disc[u] = time;
  low[u] = time;
  time++;
  foreach (int v in graph[u]) {
    if (disc[v] == -1) {
      DFS(v, u);
      low[u] = Math.Min(low[u], low[v]);
      if (low[v] > disc[u])
        bridges.Add((u, v));
    } else {
      low[u] = Math.Min(low[u], disc[v]);
    }
  }
}

medium

A. The check 'if (v == parent) continue;' is missing

B. The 'disc[u]' and 'low[u]' are not initialized before DFS

C. The 'time' variable is not incremented correctly

D. The condition 'if (low[v] > disc[u])' should be 'if (low[v] >= disc[u])'

Solution

1. Step 1: Examine the DFS traversal logic

   The code lacks 'if (v == parent) continue;' after foreach. This check prevents processing the parent edge as a back edge, which would incorrectly lower low[u] and miss bridges.

2. Step 2: Rule out other options

   The condition 'if (low[v] > disc[u])' should be 'if (low[v] >= disc[u])': 'low[v] > disc[u]' is correct for bridges (strict >). The 'disc[u]' and 'low[u]' are not initialized before DFS: disc[u] and low[u] are set inside DFS. The 'time' variable is not incremented correctly: time++ follows assignment correctly.

3. Final Answer:

   The check 'if (v == parent) continue;' is missing -> Option A

4. Quick Check:

   Parent check avoids revisiting parent [OK]

Hint: Always skip parent node in DFS to avoid false bridges [OK]

Common Mistakes:

• Forgetting to skip parent node
• Using wrong comparison operator for bridges
• Not initializing discovery times

5. You have a graph with nodes 0 to 5 and edges: (0-1), (1-2), (2-0), (1-3), (3-4), (4-5), (5-3). Using Tarjan's algorithm, which edges are bridges?

hard

A. [(1, 3)]

B. [(1, 3), (3, 4)]

C. [(1, 3), (4, 5)]

D. []

Solution

1. Step 1: Analyze graph cycles and connections

   Edges (0-1), (1-2), (2-0) form a cycle. Edges (3-4), (4-5), (5-3) form another cycle. Edge (1-3) connects these two cycles.

2. Step 2: Identify bridges

   Only edge (1-3) is a bridge; removing it disconnects {0,1,2} from {3,4,5}. Cycle edges like (3-4) are not bridges (path 3-5-4 remains), similarly for others.

3. Final Answer:

   [(1, 3)] -> Option A

4. Quick Check:

   Only edge (1-3) disconnects graph [OK]

Hint: Bridges connect cycles or leaf nodes [OK]

Common Mistakes:

• Missing bridges inside connected components
• Confusing cycle edges as bridges
• Ignoring multi-cycle connections