Connected Components Using BFS in DSA Typescript - Time & Space Complexity

Time Complexity: Connected Components Using BFS

O(n + e)

Understanding Time Complexity

We want to understand how long it takes to find all connected parts in a graph using BFS.

How does the time grow as the graph gets bigger?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

function connectedComponents(graph: Map): number {
  const visited = new Set();
  let count = 0;

  for (const node of graph.keys()) {
    if (!visited.has(node)) {
      bfs(node, graph, visited);
      count++;
    }
  }
  return count;
}

function bfs(start: number, graph: Map, visited: Set) {
  const queue: number[] = [start];
  visited.add(start);

  while (queue.length > 0) {
    const node = queue.shift()!;
    for (const neighbor of graph.get(node) || []) {
      if (!visited.has(neighbor)) {
        visited.add(neighbor);
        queue.push(neighbor);
      }
    }
  }
}
    

This code counts how many connected groups are in a graph by visiting nodes using BFS.

Identify Repeating Operations

• Primary operation: Visiting each node and its neighbors once using BFS.
• How many times: Each node and edge is checked once during the BFS traversals.

How Execution Grows With Input

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

Input Size (n nodes, e edges)	Approx. Operations
10 nodes, 15 edges	About 25 visits (nodes + edges)
100 nodes, 200 edges	About 300 visits
1000 nodes, 3000 edges	About 4000 visits

Pattern observation: The work grows roughly with the number of nodes plus edges.

Final Time Complexity

Time Complexity: O(n + e)

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

Common Mistake

[X] Wrong: "The BFS runs in O(n²) because it has nested loops."

[OK] Correct: Each edge and node is visited only once, so the total work is linear, not quadratic.

Interview Connect

Understanding BFS time complexity helps you explain graph traversal efficiency clearly and confidently.

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 does the term connected components mean in an undirected graph when using BFS?

easy

A. Groups of nodes where each node is reachable from any other node in the same group

B. Nodes that have no edges connected to them

C. The shortest path between two nodes

D. A cycle in the graph

Solution

1. Step 1: Understand connected components in undirected graphs

   Connected components are sets of nodes where each node can be reached from any other node in the same set by following edges.

2. Step 2: Relate BFS to connected components

   BFS explores all nodes reachable from a starting node, thus identifying one connected component at a time.

3. Final Answer:

   Groups of nodes where each node is reachable from any other node in the same group -> Option A

4. Quick Check:

   Connected components = reachable groups [OK]

Hint: Connected components are reachable groups of nodes [OK]

Common Mistakes:

• Confusing connected components with shortest paths
• Thinking isolated nodes are connected components with edges
• Mixing cycles with connected components

2. Which of the following is the correct TypeScript syntax to initialize a queue for BFS traversal?

easy

A. queue = new ArrayQueue();

B. const queue: number[] = [];

C. var queue = []; queue.push(1);

D. let queue = new Queue();

Solution

1. Step 1: Identify correct TypeScript array initialization

   In TypeScript, a queue for BFS can be implemented using an array: const queue: number[] = []; initializes an empty number array.

2. Step 2: Check other options for correctness

   Options A and B use undefined classes ArrayQueue and Queue which are not built-in. var queue = []; queue.push(1); uses var which is discouraged and lacks type annotation.

3. Final Answer:

   const queue: number[] = []; -> Option B

4. Quick Check:

   Array queue initialization = const queue: number[] = [] [OK]

Hint: Use typed arrays for queues in TypeScript [OK]

Common Mistakes:

• Using undefined queue classes
• Using var instead of let/const
• Not typing the queue array

3. Given the following graph adjacency list and BFS-based connected components code, what is the output?

const graph = {
  0: [1],
  1: [0, 2],
  2: [1],
  3: [4],
  4: [3]
};

function bfsComponents(graph: {[key: number]: number[]}): number[][] {
  const visited = new Set<number>();
  const components: number[][] = [];

  for (const node in graph) {
    const n = Number(node);
    if (!visited.has(n)) {
      const queue: number[] = [n];
      const component: number[] = [];
      visited.add(n);

      while (queue.length > 0) {
        const current = queue.shift()!;
        component.push(current);

        for (const neighbor of graph[current]) {
          if (!visited.has(neighbor)) {
            visited.add(neighbor);
            queue.push(neighbor);
          }
        }
      }
      components.push(component);
    }
  }
  return components;
}

console.log(bfsComponents(graph));

medium

A. [[0], [1], [2], [3], [4]]

B. [[0, 1], [2, 3, 4]]

C. [[0, 1, 2, 3, 4]]

D. [[0, 1, 2], [3, 4]]

Solution

1. Step 1: Analyze graph structure

   The graph has two connected components: nodes 0,1,2 connected together and nodes 3,4 connected together.

2. Step 2: Trace BFS traversal

   Starting from node 0, BFS visits 0, then 1, then 2. Then from node 3, BFS visits 3 and 4. So components are [[0,1,2],[3,4]].

3. Final Answer:

   [[0, 1, 2], [3, 4]] -> Option D

4. Quick Check:

   Two connected groups = [[0,1,2],[3,4]] [OK]

Hint: BFS visits all nodes in one component before next [OK]

Common Mistakes:

• Assuming all nodes are one component
• Splitting connected nodes incorrectly
• Confusing node order in output

4. The following BFS code for connected components has a bug. What is the error?

function bfsComponents(graph: {[key: number]: number[]}): number[][] {
  const visited = new Set<number>();
  const components: number[][] = [];

  for (const node in graph) {
    const n = Number(node);
    if (!visited.has(n)) {
      const queue: number[] = [n];
      const component: number[] = [];

      while (queue.length > 0) {
        const current = queue.shift()!;
        component.push(current);

        for (const neighbor of graph[current]) {
          if (!visited.has(neighbor)) {
            queue.push(neighbor);
            visited.add(neighbor);
          }
        }
      }
      components.push(component);
    }
  }
  return components;
}

medium

A. Queue is not initialized properly

B. Visited nodes are never added, causing infinite loops

C. Visited nodes are added after pushing to queue, causing duplicates

D. Component array is not pushed to components

Solution

1. Step 1: Check visited node addition timing

   Visited nodes should be marked as visited before pushing to queue to avoid duplicates.

2. Step 2: Identify the bug in code

   In the code, queue.push(neighbor) happens before visited.add(neighbor), which can cause the same neighbor to be pushed multiple times if visited check is delayed.

3. Final Answer:

   Visited nodes are added after pushing to queue, causing duplicates -> Option C

4. Quick Check:

   Mark visited before queue push to avoid duplicates [OK]

Hint: Add to visited before queue push to prevent repeats [OK]

Common Mistakes:

• Adding visited after queue push
• Not adding visited at all
• Forgetting to push neighbors

5. You have a graph with nodes 0 to 5 and edges: 0-1, 1-2, 3-4. Using BFS to find connected components, what will be the output if the graph is represented as:

const graph = {
  0: [1],
  1: [0, 2],
  2: [1],
  3: [4],
  4: [3],
  5: []
};

// BFS connected components function returns array of components

What is the correct connected components output?

hard

A. [[0, 1, 2], [3, 4], [5]]

B. [[0, 1, 2, 3, 4, 5]]

C. [[0, 1], [2, 3, 4, 5]]

D. [[0], [1], [2], [3], [4], [5]]

Solution

1. Step 1: Analyze graph edges and isolated nodes

   Nodes 0,1,2 form one connected component; nodes 3,4 form another; node 5 is isolated with no edges.

2. Step 2: Understand BFS output for connected components

   BFS will find three components: [0,1,2], [3,4], and [5] as a single-node component.

3. Final Answer:

   [[0, 1, 2], [3, 4], [5]] -> Option A

4. Quick Check:

   Isolated nodes form their own components [OK]

Hint: Isolated nodes are separate components [OK]

Common Mistakes:

• Ignoring isolated nodes
• Merging all nodes into one component
• Misgrouping connected nodes