Magnificent Dijkstra Algorithm Test - 54+ MCQs: High Difficulty Dijkstra Algorithm Quiz: Test Your Graph Algorithm Knowledge

1. How does Dijkstra's algorithm handle unreachable vertices?

It ignores them and continues with reachable vertices

It assigns an infinite distance to them

It removes them from the graph

It terminates with an error message

2. In Dijkstra's algorithm, how are ties broken when multiple paths have the same minimum distance?

Randomly

Based on vertex ID

Based on the weight of the last edge

In a first-come, first-served manner

3. In Dijkstra's algorithm, what is the role of the 'visited' set?

To keep track of all vertices in the graph

To mark vertices that have been explored

To store the shortest paths between vertices

To identify vertices with the highest weights

4. What is the primary advantage of using Dijkstra's algorithm over other pathfinding algorithms in certain scenarios?

Efficiency on dense graphs

Efficiency on sparse graphs

Handling of negative edge weights

Adaptability to dynamic graphs

5. What is the significance of the 'parent' attribute in the context of Dijkstra's algorithm?

To store the final shortest paths

To track the order of vertex visits

To maintain the graph structure

To build the shortest path tree

6. How does the presence of parallel edges impact Dijkstra's algorithm?

It enhances the algorithm's speed

It has no impact on the algorithm

It requires additional preprocessing

It leads to incorrect results

7. Which algorithm is often compared to Dijkstra's algorithm for finding the shortest path?

Bellman-Ford algorithm

Prim's algorithm

Floyd-Warshall algorithm

Kruskal's algorithm

8. How does Dijkstra's algorithm handle negative edge weights in a graph?

It ignores negative weights

It converts negative weights to positive

It doesn't work with negative weights

It adjusts the algorithm to handle negative weights

9. What is the significance of the 'd' and 'π' arrays in Dijkstra's algorithm?

'd' stores the shortest distance to each vertex, 'π' stores the predecessor

'd' stores the discovery time of each vertex, 'π' stores the parent

'd' stores the density of each vertex, 'π' stores the probability

'd' stores the direction of each vertex, 'π' stores the path

10. What modification is needed in Dijkstra's algorithm to handle graphs with negative edge weights?

None, it inherently supports negative weights

Adjustment in the relaxation step

Introduction of a bias factor

Replacement of the priority queue

11. How does Dijkstra's algorithm handle graphs with disconnected components?

It connects them with dummy edges

It marks them as unreachable

It processes each component independently

It returns an error

12. How does the choice of data structure for the priority queue affect the time complexity of Dijkstra's algorithm?

No impact on time complexity

Linear impact on time complexity

Exponential impact on time complexity

Logarithmic impact on time complexity

13. In the context of Dijkstra's algorithm, what is the purpose of the 'marked' attribute for vertices?

To identify unreachable vertices

To indicate visited vertices

To store final distances

To optimize priority queue operations

14. What is the purpose of the 'source' parameter in Dijkstra's algorithm?

To specify the destination vertex

To specify the starting vertex

To specify the target weight

To specify the maximum path length

15. What is the significance of the term 'single-source' in the context of Dijkstra's algorithm?

It refers to finding the shortest path between any pair of vertices

It focuses on exploring only one vertex at a time

It requires a single priority queue for efficiency

It solves the problem of finding the shortest path from one vertex to all others

16. What is the primary difference between Dijkstra's algorithm and A* algorithm?

Dijkstra's algorithm uses heuristics, A* does not

A* algorithm is only applicable to weighted graphs

Dijkstra's algorithm guarantees the shortest path, A* does not

A* algorithm incorporates a heuristic to prioritize paths

17. What is the primary advantage of using a Fibonacci Heap in Dijkstra's algorithm?

It guarantees the shortest path

It has lower time complexity than other heaps

It allows for efficient decrease key operations

It eliminates the need for priority queues

18. What is the key concept behind Dijkstra's algorithm for finding the shortest path?

Breadth-first search

Greedy strategy

Depth-first search

Dynamic programming

19. What is the time complexity of Dijkstra's algorithm with an adjacency matrix representation?

O(V log V)

O(E log V)

O(V^2)

O(E + V)

20. What is the impact of using a priority queue with insufficient priority updates in Dijkstra's algorithm?

Algorithm becomes slower

Algorithm becomes faster

Algorithm becomes less accurate

Algorithm becomes more accurate

21. Which algorithm is an alternative to Dijkstra's algorithm for graphs with negative edge weights?

Floyd-Warshall algorithm

Depth-First Search

Breadth-First Search

Prim's algorithm

22. How does Dijkstra's algorithm handle graphs with multiple shortest paths between two vertices?

It returns any valid shortest path

It selects the shortest path randomly

It returns all possible shortest paths

It fails to handle multiple shortest paths

23. In a weighted graph, what does the term 'weight' typically represent in the context of Dijkstra's algorithm?

Number of edges

Euclidean distance

Traversal cost

Numeric value assigned to an edge

24. What is the main drawback of using Dijkstra's algorithm in a dynamic graph that undergoes frequent edge weight updates?

High space complexity

Inability to handle dynamic graphs

Slow convergence

Recomputation of distances

25. How does Dijkstra's algorithm behave when all edge weights are equal?

It produces random paths

It finds the longest path

It terminates with an error

It behaves like Breadth-First Search

26. How does Dijkstra's algorithm behave when there is a negative cycle in the graph?

It terminates with an error

It enters an infinite loop

It ignores the negative cycle

It correctly handles negative cycles

27. What condition must be satisfied for Dijkstra's algorithm to guarantee the correct shortest paths?

The graph must be connected

The graph must be acyclic

The edge weights must be positive

The graph must be a tree

28. What is the key challenge in implementing Dijkstra's algorithm in a distributed computing environment?

Communication overhead

Lack of parallelization

Memory constraints

Synchronization issues

29. What is the primary purpose of Dijkstra's algorithm?

Finding the shortest path in a weighted graph

Sorting elements in an array

Searching for a specific node in a tree

Detecting cycles in a graph

30. How does Dijkstra's algorithm handle graphs with unconnected vertices?

It ignores unconnected vertices

It connects them with dummy edges

It marks them as unreachable

It returns an error

Dijkstra Algorithm MCQ Test 3