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

1. 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

2. What is the primary limitation of using Dijkstra's algorithm in large-scale networks?

It becomes computationally expensive

It tends to produce inaccurate results

It is incompatible with parallel processing

It is sensitive to changes in edge weights

3. 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

4. What scenario would make Dijkstra's algorithm less efficient?

When the graph has a single connected component

When the graph is unweighted

When the graph has a large number of vertices

When the graph has a large number of edges

5. In the context of Dijkstra's algorithm, what does 'SPT' stand for?

Shortest Path Tree

Simple Path Traversal

Sequential Path Tree

Strongly-Connected Path Tree

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

Breadth-first search

Greedy strategy

Depth-first search

Dynamic programming

7. 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

8. 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

9. 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

10. In the Dijkstra algorithm, what does the term 'distance' refer to?

Number of vertices

Edge weight

Number of edges

Graph diameter

11. In Dijkstra's algorithm, what happens if a shorter path to a vertex is found after it has been added to the priority queue?

It is ignored

It is added to the back of the priority queue

It triggers a recalculation of the entire path

It is considered and the priority queue is updated accordingly

12. What modification is needed in Dijkstra's algorithm to support parallel processing?

Parallelize the relaxation step

Sequential execution is sufficient

Parallelize the initialization step

Use multi-threading for priority queue operations

13. What is the significance of the term 'greedy' in describing Dijkstra's algorithm?

It always chooses the path with the highest weight

It makes the locally optimal choice at each step

It backtracks to correct suboptimal choices

It considers all possible paths before choosing one

14. In Dijkstra's algorithm, what does the term 'relaxation' refer to?

Adjusting the distance estimate of a vertex if a shorter path is found

Adding a new node to the graph

Removing edges with higher weights

Calculating the average distance of the graph

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

Communication overhead

Lack of parallelization

Memory constraints

Synchronization issues

16. 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

17. What is the significance of the 'relaxation' step in Dijkstra's algorithm?

To update the distance values

To reset the visited status

To reorganize the graph structure

To handle negative edge weights

18. 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

19. 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

20. What is the purpose of the priority queue in Dijkstra's algorithm?

To store all vertices in random order

To store vertices based on their discovery time

To store vertices based on their topological order

To efficiently extract the minimum distance vertex

21. 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

22. 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

23. What is the time complexity of Dijkstra's algorithm when implemented with a binary heap?

O(V^2)

O(V log V)

O(E + V log V)

O(E log V)

24. 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

25. 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

26. How does Dijkstra's algorithm handle graphs with cycles?

It ignores cycles and proceeds with the shortest path

It terminates if a cycle is detected

It collapses cycles into single vertices

It always chooses the path with the fewest cycles

27. What is the role of a 'heap' data structure in optimizing Dijkstra's algorithm?

To minimize space complexity

To efficiently extract minimum values

To avoid negative cycles

To handle disconnected components

28. 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

29. 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

30. 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)

31. 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

32. 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

33. 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

34. 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

35. What is the significance of the 'infinity' value in the initialization of distances in Dijkstra's algorithm?

It indicates unreachable vertices

It represents an undefined distance

It facilitates parallel processing

It is used for prioritization

36. How does the choice of initial vertex impact the results of Dijkstra's algorithm?

No impact on the results

It determines the starting point of the traversal

It affects the final distance values

It leads to different shortest paths

37. When is Dijkstra's algorithm preferred over Bellman-Ford algorithm?

When the graph has negative edge weights

When the graph is unweighted

When the graph has cycles

When finding the shortest path from a single source to all vertices

38. What is the purpose of the 'visited' set in Dijkstra's algorithm?

To store the final shortest paths

To mark vertices that have been processed

To track the order of vertex visits

To keep track of backtracking

39. 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

40. Which data structure is commonly used to implement Dijkstra's algorithm efficiently?

Array

Queue

Stack

Priority Queue

41. What is the main drawback of Dijkstra's algorithm?

It cannot handle graphs with negative edge weights

It has high time complexity for dense graphs

It is prone to infinite loop errors

It is not suitable for directed graphs

42. 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

43. In Dijkstra's algorithm, what data structure is commonly used to efficiently extract the minimum distance node?

Queue

Stack

Priority Queue

Linked List

44. 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

45. What is the primary limitation of Dijkstra's algorithm when dealing with large graphs?

Exponential time complexity

Inability to handle disconnected graphs

Memory consumption

Quadratic time complexity

46. 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

47. 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

48. Which step in Dijkstra's algorithm is responsible for selecting the next vertex to process?

Initialization

Relaxation

Termination

Priority queue extraction

49. 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

50. 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

Dijkstra Algorithm MCQ Test 1