Articulation Points in Graph in DSA Typescript - Time & Space Complexity

Time Complexity: Articulation Points in Graph

O(n + m)

Understanding Time Complexity

We want to understand how the time needed to find articulation points changes as the graph grows.

Specifically, how does the algorithm's work increase with more nodes and edges?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

function findArticulationPoints(graph: number[][]): number[] {
  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);
  const parent = new Array(n).fill(-1);
  const ap = new Array(n).fill(false);
  let time = 0;

  function dfs(u: number) {
    visited[u] = true;
    disc[u] = low[u] = ++time;
    let children = 0;
    for (const v of graph[u]) {
      if (!visited[v]) {
        children++;
        parent[v] = u;
        dfs(v);
        low[u] = Math.min(low[u], low[v]);
        if (parent[u] === -1 && children > 1) ap[u] = true;
        if (parent[u] !== -1 && low[v] >= disc[u]) ap[u] = true;
      } else if (v !== parent[u]) {
        low[u] = Math.min(low[u], disc[v]);
      }
    }
  }

  for (let i = 0; i < n; i++) {
    if (!visited[i]) dfs(i);
  }

  return ap.map((isAp, idx) => isAp ? idx : -1).filter(x => x !== -1);
}
    

This code finds all articulation points in a 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 its neighbors.
• How many times: Each node and edge is visited once during DFS traversal.

How Execution Grows With Input

As the graph grows, the algorithm visits every node and edge once.

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

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

Final Time Complexity

Time Complexity: O(n + m)

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

Common Mistake

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

[OK] Correct: The DFS only visits each edge and node once, not every pair, so it is more efficient than checking all pairs.

Interview Connect

Understanding this linear time complexity helps you explain how graph traversal algorithms efficiently find key points in networks.

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 an articulation point (or cut vertex) in a graph?

easy

A. A vertex that, when removed, increases the number of connected components

B. A vertex with the highest degree in the graph

C. A vertex connected to all other vertices

D. A vertex that has no edges connected to it

Solution

1. Step 1: Understand the definition of articulation point

   An articulation point is a vertex that, if removed, breaks the graph into more pieces (connected components).

2. Step 2: Compare options with definition

   Only A vertex that, when removed, increases the number of connected components matches this definition exactly.

3. Final Answer:

   A vertex that, when removed, increases the number of connected components -> Option A

4. Quick Check:

   Articulation point = vertex increasing components when removed [OK]

Hint: Articulation point breaks graph connectivity when removed [OK]

Common Mistakes:

• Confusing articulation point with highest degree vertex
• Thinking articulation point connects to all vertices
• Assuming isolated vertex is articulation point

2. Which of the following is the correct TypeScript function signature to find articulation points in an undirected graph represented as adjacency list?

easy

A. function findArticulationPoints(graph: number): number[]

B. function findArticulationPoints(graph: number[][]): void

C. function findArticulationPoints(graph: string): number[]

D. function findArticulationPoints(graph: Map): number[]

Solution

1. Step 1: Identify the graph representation type

   An adjacency list is best represented as a Map from node number to array of connected nodes.

2. Step 2: Check function signature compatibility

   function findArticulationPoints(graph: Map): number[] uses Map and returns number[] which fits the problem.

3. Final Answer:

   function findArticulationPoints(graph: Map<number, number[]>): number[] -> Option D

4. Quick Check:

   Adjacency list as Map with number arrays returns number array [OK]

Hint: Use Map for adjacency list in TypeScript [OK]

Common Mistakes:

• Using string type for graph input
• Returning void instead of list of articulation points
• Passing graph as a single number

3. Given the following TypeScript code snippet to find articulation points, what will be the output for the graph edges: [[0,1],[1,2],[2,0],[1,3]]?

const graph = new Map();
graph.set(0, [1, 2]);
graph.set(1, [0, 2, 3]);
graph.set(2, [0, 1]);
graph.set(3, [1]);

const articulationPoints = findArticulationPoints(graph);
console.log(articulationPoints);

medium

A. [0, 1]

B. [3]

C. [1]

D. []

Solution

1. Step 1: Analyze the graph structure

   The graph has a triangle between 0,1,2 and a leaf node 3 connected to 1.

2. Step 2: Identify articulation points

   Removing node 1 disconnects node 3 from the rest, so 1 is an articulation point. Nodes 0 and 2 are part of a cycle, so not articulation points. Node 3 is a leaf, not articulation point.

3. Final Answer:

   [1] -> Option C

4. Quick Check:

   Only node 1 disconnects graph when removed [OK]

Hint: Check if removing node splits graph into more parts [OK]

Common Mistakes:

• Thinking nodes in cycle are articulation points
• Including leaf nodes as articulation points
• Ignoring connectivity after removal

4. The following TypeScript code attempts to find articulation points but has a bug. What is the bug?

function dfs(u: number, parent: number) {
  visited[u] = true;
  disc[u] = time;
  low[u] = time;
  time++;
  let children = 0;
  for (const v of graph.get(u) || []) {
    if (!visited[v]) {
      children++;
      dfs(v, u);
      low[u] = Math.min(low[u], low[v]);
      if (parent !== -1 && low[v] >= disc[u]) {
        articulationPoints.add(u);
      }
    } else if (v !== parent) {
      low[u] = Math.min(low[u], disc[v]);
    }
  }
  if (parent === -1 && children > 1) {
    articulationPoints.add(u);
  }
}

medium

A. The 'visited' array is not initialized before DFS

B. The root node condition for articulation point is checked after the loop

C. The variable 'time' is not incremented correctly

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

Solution

1. Step 1: Review DFS variables initialization

   The code uses 'visited' array but does not show its initialization before DFS calls.

2. Step 2: Identify missing initialization impact

   If 'visited' is not initialized to false for all nodes, DFS may skip nodes or behave incorrectly.

3. Final Answer:

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

4. Quick Check:

   Uninitialized visited array causes DFS errors [OK]

Hint: Always initialize visited array before DFS traversal [OK]

Common Mistakes:

• Assuming time increments incorrectly
• Misunderstanding root node articulation condition
• Changing condition from >= to > incorrectly

5. You have a network of computers represented as an undirected graph. You want to find all critical computers whose failure would split the network. The graph has 7 nodes with edges: [[0,1],[1,2],[2,0],[1,3],[3,4],[4,5],[5,3],[4,6]]. Which nodes are articulation points?

hard

A. [0, 2, 5]

B. [1, 3, 4]

C. [3, 5, 6]

D. [1, 4, 6]

Solution

1. Step 1: Analyze graph components and cycles

   Nodes 0,1,2 form a triangle (cycle). Nodes 3,4,5 form another cycle. Node 6 is connected only to 4.

2. Step 2: Identify articulation points

   Removing 1 disconnects node 3 and its cycle from 0,2. Removing 3 disconnects 4,5,6 from 1. Removing 4 disconnects node 6 from rest. So articulation points are 1, 3, and 4.

3. Final Answer:

   [1, 3, 4] -> Option B

4. Quick Check:

   Nodes connecting cycles and leaf nodes are articulation points [OK]

Hint: Look for nodes connecting cycles or leaf nodes [OK]

Common Mistakes:

• Including nodes inside cycles as articulation points
• Missing nodes connecting leaf nodes
• Confusing leaf nodes as articulation points