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Graph Theory

50 Graph Theory interview questions

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Introduction to Graphs


  • 1.

    What is a Graph?

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  • 2.

    What are some common Types and Categories of Graphs?

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  • 3.

    What is the difference between a Tree and a Graph?

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  • 4.

    How can you determine the Minimum number of edges for a graph to remain connected?

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  • 5.

    Define Euler Path and Euler Circuit in the context of graph theory.

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Graph Representations


  • 6.

    Compare Adjacency Lists and Adjacency Matrices for graph representation.

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  • 7.

    What is an Incidence Matrix, and when would you use it?

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  • 8.

    Discuss Edge List as a graph representation and its use cases.

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  • 9.

    Explain how to save space while storing a graph using Compressed Sparse Row (CSR).

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Graph Traversal Algorithms


  • 10.

    Explain the Breadth-First Search (BFS) traversing method.

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  • 11.

    Explain the Depth-First Search (DFS) algorithm.

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  • 12.

    What are the key differences between BFS and DFS?

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  • 13.

    Implement a method to check if there is a Path between two vertices in a graph.

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  • 14.

    Solve the problem of printing all Paths from a source to destination in a Directed Graph with BFS or DFS.

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Graph Properties and Types


  • 15.

    What is a Bipartite Graph? How to detect one?

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  • 16.

    Define Cyclic and Acyclic graphs and explain how to identify them.

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  • 17.

    Explain Planar graphs and the conditions that make a graph planar.

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  • 18.

    What are Dense and Sparse graphs? Discuss their density measures and typical use cases.

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Graph Algorithms and Complexity


  • 19.

    Why the complexity of DFS is O(V+E)?

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  • 20.

    Provide an implementation for Topological Sort in a Directed Acyclic Graph (DAG).

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  • 21.

    Write an algorithm to detect a Cycle in an undirected graph.

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  • 22.

    Discuss the complexity of finding All Pair Shortest Paths in a weighted graph.

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Memory and Performance in Graph Operations


  • 23.

    Why does Breadth-First Search use more memory than Depth-First Search?

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  • 24.

    Illustrate the difference in Peak Memory Consumption between DFS and BFS.

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  • 25.

    How can Graph Data Structures be optimized for better Cache Locality?

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  • 26.

    Discuss methods to Reduce Memory Usage in graph representations.

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Shortest Path Algorithms


  • 27.

    What is the difference between BFS and Dijkstra’s algorithms when looking for the shortest path?

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  • 28.

    Implement Dijkstra’s Algorithm for finding the shortest path in a graph with non-negative edge weights.

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  • 29.

    How does Bellman-Ford Algorithm differ from Dijkstra’s and where would you use it?

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  • 30.

    Explain the concept of Floyd-Warshall Algorithm and its usage.

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Heuristic-Based Graph Search Algorithms


  • 31.

    What is A* Search?

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  • 32.

    What is the heuristic cost function in A* Search?

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  • 33.

    Explain the difference between Best-First Search and A* Search.

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  • 34.

    Provide an implementation of the Greedy Best-First Search and compare it to A*.

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  • 35.

    How can you adapt A* Search to work on a puzzle game like Sudoku?

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Real-World Applications of Graphs


  • 36.

    What are some real-world Applications of Graphs?

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  • 37.

    Provide some practical examples of using Depth-First Search vs Breadth-First Search.

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  • 38.

    How do social networks use graphs for recommendations and features like friend suggestions?

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  • 39.

    Explain how a GPS navigation system might use graph data structures and algorithms.

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Advanced Graph Topics


  • 40.

    What is a Graph Embedding, and how is it applicable in machine learning?

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  • 41.

    Describe the Min-Cut Max-Flow Theorem and its significance in network flow problems.

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  • 42.

    Discuss the concept of Edge Coloring and its applications.

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  • 43.

    Implement an algorithm that finds the Minimum Spanning Tree of a graph.

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  • 44.

    Explain the importance of Graph Databases and how they differ from traditional relational databases.

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Algorithms for Specific Graph Classes


  • 45.

    Discuss how algorithms might vary when dealing with Weighted vs Unweighted Graphs.

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  • 46.

    What special considerations are needed when implementing algorithms for Directed vs Undirected Graphs?

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  • 47.

    Provide an efficient algorithm for finding Articulation Points in a graph.

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Graph Challenges and Problem-Solving


  • 48.

    Solve the Knight’s tour problem using graph traversal techniques.

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  • 49.

    How would you design an algorithm to evaluate the connected components of an undirected graph?

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  • 50.

    Implement a graph solution for the River Crossing Problem.

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