Bridges in Graph Tarjan's Algorithm in DSA Javascript - 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 Tarjan's algorithm perform when checking all connections?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

function findBridges(graph) {
  const n = graph.length;
  const visited = new Array(n).fill(false);
  const disc = new Array(n).fill(-1);
  const low = new Array(n).fill(-1);
  let time = 0;
  const bridges = [];

  function dfs(u, parent) {
    visited[u] = true;
    disc[u] = low[u] = time++;
    for (const v of graph[u]) {
      if (!visited[v]) {
        dfs(v, u);
        low[u] = Math.min(low[u], low[v]);
        if (low[v] > disc[u]) bridges.push([u, v]);
      } else if (v !== parent) {
        low[u] = Math.min(low[u], disc[v]);
      }
    }
  }

  for (let i = 0; i < n; i++) {
    if (!visited[i]) dfs(i, -1);
  }
  return bridges;
}
    

This code finds all bridges (critical connections) in an undirected graph using depth-first search and tracking discovery and low times.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: Depth-first search (DFS) visits each node and explores all its edges.
• How many times: Each node is visited once, and each edge is checked once during DFS.

How Execution Grows With Input

As the graph grows with more nodes and edges, the algorithm visits each node once and checks each edge once.

Input Size (n nodes, m edges)	Approx. Operations
10 nodes, 15 edges	About 10 visits + 15 edge checks = 25 operations
100 nodes, 200 edges	About 100 visits + 200 edge checks = 300 operations
1000 nodes, 5000 edges	About 1000 visits + 5000 edge checks = 6000 operations

Pattern observation: The operations grow roughly in proportion to the sum of nodes and edges.

Final Time Complexity

Time Complexity: O(n + m)

This means the time grows linearly with the number of nodes plus the number of 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 visits each node once and explores edges directly connected to it, not all pairs. So it depends on actual edges, not all pairs.

Interview Connect

Understanding this linear time complexity helps you explain how efficient graph algorithms work in real problems, showing you can handle large data without slowdowns.

Self-Check

"What if the graph was directed instead of undirected? 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 detect cycles in a graph

B. To identify edges that, if removed, increase the number of connected components

C. To find the shortest path between two nodes

D. To count the total number of nodes in the graph

Solution

1. Step 1: Understand the definition of a bridge

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

2. Step 2: Relate Tarjan's algorithm to bridges

   Tarjan's algorithm efficiently finds such edges by using DFS and tracking discovery and low times.

3. Final Answer:

   To identify edges that, if removed, increase the number of connected components -> Option B

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
• Assuming it counts nodes

2. Which of the following is the correct way to initialize the discovery time array in JavaScript for Tarjan's algorithm?

easy

A. const disc = new Array(n).fill(-1);

B. const disc = Array(n).map(() => 0);

C. const disc = new Array(n).map(0);

D. const disc = Array.fill(n, -1);

Solution

1. Step 1: Understand array initialization in JavaScript

   Using new Array(n).fill(value) correctly fills all elements with the given value.

2. Step 2: Check each option

   A: const disc = new Array(n).fill(-1); correctly creates an array of length n filled with -1. B: const disc = Array(n).map(() => 0); fills with 0 instead of -1. C: const disc = new Array(n).map(0); passes non-function to map, causing TypeError. D: const disc = Array.fill(n, -1); uses incorrect syntax (no static Array.fill).

3. Final Answer:

   const disc = new Array(n).fill(-1); -> Option A

4. Quick Check:

   Use fill() to initialize arrays [OK]

Hint: Use new Array(n).fill(value) to initialize arrays [OK]

Common Mistakes:

• Initializing with 0 instead of -1
• Passing non-function to map
• Wrong syntax for Array.fill

3. What will be the output bridges found by the following code snippet for the graph edges: [[0,1],[1,2],[2,0],[1,3]]?

const graph = [[1],[0,2,3],[1,0],[1]];
// Assume Tarjan's algorithm is correctly implemented and called
// Output bridges are printed as pairs of nodes

medium

A. []

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

C. [[0,1],[1,2],[2,0]]

D. [[1,3]]

Solution

1. Step 1: Analyze the graph structure

   The graph has a triangle between nodes 0,1,2 and a single edge from 1 to 3.

2. Step 2: Identify bridges

   The triangle edges are part of a cycle, so none are bridges. The edge [1,3] connects node 3 alone, so removing it increases components.

3. Final Answer:

   [[1,3]] -> Option D

4. Quick Check:

   Only edge to isolated node is bridge [OK]

Hint: Edges in cycles are not bridges [OK]

Common Mistakes:

• Marking cycle edges as bridges
• Ignoring isolated node connections
• Confusing node indices

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

function dfs(u, parent) {
  visited[u] = true;
  disc[u] = low[u] = time++;
  for (const v of graph[u]) {
    if (!visited[v]) {
      dfs(v, u);
      low[u] = Math.min(low[u], low[v]);
      if (low[v] > disc[u]) {
        bridges.push([u, v]);
      }
    } else if (v !== parent) {
      low[u] = Math.min(low[u], disc[v]);
    }
  }
}

medium

A. The 'visited' array is not initialized

B. The condition 'low[v] > disc[u]' should be 'low[v] >= disc[u]'

C. The 'time' variable is not incremented correctly

D. The else if condition should check 'v === parent' instead of 'v !== parent'

Solution

1. Step 1: Check variable initialization

   The code uses 'visited' array but does not show its initialization, which is necessary before DFS.

2. Step 2: Verify other parts

   The condition 'low[v] > disc[u]' is correct for bridges. The time variable is incremented properly. The else if condition correctly checks 'v !== parent'.

3. Final Answer:

   The 'visited' array is not initialized -> Option A

4. Quick Check:

   Initialize visited before DFS [OK]

Hint: Always initialize visited array before DFS [OK]

Common Mistakes:

• Changing correct bridge condition
• Misunderstanding parent check
• Forgetting to initialize arrays

5. Given a graph with nodes 0 to 4 and edges [[0,1],[1,2],[2,0],[1,3],[3,4]], which edges are bridges using Tarjan's algorithm?

hard

A. [[0,1],[1,2],[2,0]]

B. [[0,1],[3,4]]

C. [[1,3],[3,4]]

D. [[1,2],[1,3]]

Solution

1. Step 1: Analyze the graph structure

   Nodes 0,1,2 form a cycle, so edges among them are not bridges. Edges [1,3] and [3,4] connect nodes outside the cycle.

2. Step 2: Identify bridges

   Removing [1,3] or [3,4] increases connected components, so these are bridges.

3. Final Answer:

   [[1,3],[3,4]] -> Option C

4. Quick Check:

   Edges connecting cycle to outside are bridges [OK]

Hint: Edges outside cycles connecting nodes are bridges [OK]

Common Mistakes:

• Marking cycle edges as bridges
• Ignoring edges connecting outside nodes
• Confusing node indices