Cycle Detection in Undirected Graph in DSA Java - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is a cycle in an undirected graph?

A cycle is a path that starts and ends at the same vertex, with all edges and vertices distinct except the first and last vertex.

beginner

Which data structure is commonly used to detect cycles in an undirected graph?

Depth-First Search (DFS) is commonly used to detect cycles by checking if a visited vertex is encountered again and is not the parent of the current vertex.

intermediate

Why do we need to track the parent vertex during DFS in cycle detection?

Tracking the parent vertex helps to ignore the edge leading back to the immediate predecessor, preventing false detection of a cycle.

intermediate

What is the time complexity of cycle detection in an undirected graph using DFS?

The time complexity is O(V + E), where V is the number of vertices and E is the number of edges, because each vertex and edge is visited once.

beginner

Explain the role of the visited array in cycle detection using DFS.

The visited array keeps track of which vertices have been explored to avoid revisiting and to detect if a vertex is encountered again indicating a cycle.

What does it mean if during DFS you visit a vertex that is already visited and is not the parent?

A A cycle is detected

B Graph is disconnected

C No cycle detected

D Graph is directed

Visiting an already visited vertex that is not the parent means a cycle exists.

Which of the following is NOT required for cycle detection in an undirected graph using DFS?

A Visited array

B Parent tracking

C Queue data structure

D Graph adjacency list or matrix

Queue is not required; DFS uses recursion or stack, not a queue.

What is the initial state of the visited array before DFS starts?

A All true

B All false

C Random values

D Half true, half false

Initially, no vertices are visited, so all values are false.

If a graph has no cycles, what will DFS traversal show?

A It will revisit vertices

B It will fail to visit all vertices

C It will detect cycles

D It will never visit a vertex twice except parent

DFS visits each vertex once; revisiting only happens through parent edges.

What is the best way to represent an undirected graph for cycle detection?

A Adjacency list

B Adjacency matrix

C Edge list only

D None of the above

Adjacency list is efficient for DFS and cycle detection.

Describe the step-by-step process of detecting a cycle in an undirected graph using DFS.

Think about how DFS explores neighbors and tracks parents.

Explain why tracking the parent vertex is important in cycle detection for undirected graphs.

Consider what happens when DFS returns to the vertex it came from.

Practice

1. What is the main idea behind detecting a cycle in an undirected graph using DFS?

easy

A. If the graph has more edges than nodes, it always has a cycle.

B. If all nodes are visited exactly once, the graph has a cycle.

C. If the graph is disconnected, it contains a cycle.

D. If we visit a node that is already visited and is not the parent, a cycle exists.

Solution

1. Step 1: Understand DFS traversal in undirected graph

   DFS visits nodes and tracks the parent node to avoid false cycle detection.

2. Step 2: Detect cycle condition

   If during DFS, a visited node is found that is not the parent, it means a back edge exists, indicating a cycle.

3. Final Answer:

   If we visit a node that is already visited and is not the parent, a cycle exists. -> Option D

4. Quick Check:

   Cycle detection in undirected graph = check visited node not parent [OK]

Hint: Check visited nodes excluding parent during DFS to find cycles [OK]

Common Mistakes:

• Confusing parent node with visited node
• Assuming disconnected graph always has cycles
• Thinking more edges than nodes always means cycle

2. Which of the following Java method signatures is correct for a DFS function used in cycle detection in an undirected graph?

easy

A. boolean dfs(int node, boolean[] visited, List graph)

B. void dfs(int node, int parent, boolean[] visited, List<Integer> graph)

C. boolean dfs(int node, int parent, boolean[] visited, List graph)

D. int dfs(int node, int parent, boolean[] visited, List graph)

Solution

1. Step 1: Identify parameters needed for DFS cycle detection

   DFS needs current node, parent node, visited array, and adjacency list graph.

2. Step 2: Check return type and parameter types

   Return type boolean indicates if cycle found; graph must be List of Lists for adjacency; parent is needed.

3. Final Answer:

   boolean dfs(int node, int parent, boolean[] visited, List<List<Integer>> graph) -> Option C

4. Quick Check:

   DFS signature with parent and boolean return = boolean dfs(int node, int parent, boolean[] visited, List graph) [OK]

Hint: DFS needs parent node and boolean return for cycle detection [OK]

Common Mistakes:

• Using void return type instead of boolean
• Passing graph as List<Integer> instead of List
• Omitting parent parameter

3. What will be the output of the following Java code snippet detecting cycle in an undirected graph?

import java.util.*;
public class GraphCycle {
    static boolean dfs(int node, int parent, boolean[] visited, List graph) {
        visited[node] = true;
        for (int adj : graph.get(node)) {
            if (!visited[adj]) {
                if (dfs(adj, node, visited, graph)) return true;
            } else if (adj != parent) {
                return true;
            }
        }
        return false;
    }
    public static void main(String[] args) {
        int n = 4;
        List graph = new ArrayList<>();
        for (int i = 0; i < n; i++) graph.add(new ArrayList<>());
        graph.get(0).add(1); graph.get(1).add(0);
        graph.get(1).add(2); graph.get(2).add(1);
        graph.get(2).add(3); graph.get(3).add(2);
        graph.get(3).add(1); graph.get(1).add(3);
        boolean[] visited = new boolean[n];
        boolean hasCycle = false;
        for (int i = 0; i < n; i++) {
            if (!visited[i]) {
                if (dfs(i, -1, visited, graph)) {
                    hasCycle = true;
                    break;
                }
            }
        }
        System.out.println(hasCycle);
    }
}

medium

A. true

B. false

C. Compilation error

D. Runtime exception

Solution

1. Step 1: Analyze graph edges and structure

   Graph edges: 0-1, 1-2, 2-3, 3-1 form a cycle (1-2-3-1).

2. Step 2: Trace DFS cycle detection logic

   DFS finds visited node 1 again from 3 (not parent), so returns true indicating cycle.

3. Final Answer:

   true -> Option A

4. Quick Check:

   Cycle detected in graph = true [OK]

Hint: Look for back edge to visited node not parent to confirm cycle [OK]

Common Mistakes:

• Ignoring the edge 3-1 that closes the cycle
• Assuming no cycle because graph is connected
• Misunderstanding parent check in DFS

4. Identify the bug in the following Java code snippet for cycle detection in an undirected graph:

boolean dfs(int node, int parent, boolean[] visited, List graph) {
    visited[node] = true;
    for (int adj : graph.get(node)) {
        if (!visited[adj]) {
            dfs(adj, node, visited, graph);
        } else if (adj != parent) {
            return true;
        }
    }
    return false;
}

medium

A. Incorrect parent check condition

B. Missing return statement for recursive dfs call result

C. Visited array not updated correctly

D. Graph adjacency list type is wrong

Solution

1. Step 1: Review recursive DFS calls

   Recursive call dfs(adj, node, visited, graph) is made but its boolean result is ignored.

2. Step 2: Understand impact of ignoring return value

   If a cycle is detected deeper, it won't propagate true back, causing false negatives.

3. Final Answer:

   Missing return statement for recursive dfs call result -> Option B

4. Quick Check:

   Return recursive call result to detect cycles correctly [OK]

Hint: Always return recursive DFS call result when checking for cycles [OK]

Common Mistakes:

• Not returning true from recursive calls
• Confusing parent check logic
• Not marking nodes visited before recursion

5. Given an undirected graph represented as adjacency list:

0: [1, 2]
1: [0, 3]
2: [0, 3]
3: [1, 2, 4]
4: [3]

Which of the following modifications will correctly detect a cycle in this graph using DFS cycle detection method?

hard

A. Start DFS from node 0 and pass -1 as parent; check visited nodes for back edges.

B. Start DFS from node 4 only; ignore parent parameter in DFS calls.

C. Use BFS instead of DFS without parent tracking to detect cycles.

D. Mark nodes visited after all recursive calls complete.

Solution

1. Step 1: Understand graph structure and cycle presence

   Edges form a cycle: 0-1-3-2-0. Starting DFS from 0 covers all nodes.

2. Step 2: Apply correct DFS cycle detection method

   Starting DFS from 0 with parent -1 and checking visited nodes excluding parent detects cycle correctly.

3. Final Answer:

   Start DFS from node 0 and pass -1 as parent; check visited nodes for back edges. -> Option A

4. Quick Check:

   Proper DFS start and parent check detects cycle [OK]

Hint: Start DFS from any node with parent -1 and track visited nodes [OK]

Common Mistakes:

• Ignoring parent parameter causing false positives
• Starting DFS from leaf node only
• Marking visited nodes too late