500+ Trees (Data Structure) MCQs with FREE PDF

We have the best collection of Trees (Data Structure) MCQs and answer with FREE PDF. These Trees (Data Structure) MCQs will help you to prepare for any competitive exams like: BCA, MCA, GATE, GRE, IES, PSC, UGC NET, DOEACC Exams at all levels – you just have to practice regularly.

Trees (Data Structure) MCQs

1. How many child nodes does each node of Ternary Tree contain?

a) 4

b) 6

c) 5

d) 3

Answer: 3

2. Which of the following is the name of the node having child nodes?

a) Brother

b) Sister

c) Mother

d) Parent

Answer: Parent

3. What is the depth of the root node of the ternary tree?

a) 2

b) 1

c) 0

d) 3

Answer: 0

4. How many extra nodes are there in Full ternary tree than a complete ternary tree?

a) 1

b) 2

c) 3

d) Both have same number of nodes

Answer: Both have same number of nodes

5. Can leaf node be called child node in a ternary tree?

a) True

b) False

Answer: True

6. Can child node be always called Leaf node in the ternary tree?

a) True

b) False

Answer: False

7. Which of the following is the implementation of the ternary tree?

a) AVL Tree

b) Ternary Heap

c) Hash Table

d) Dictionary

Answer: Ternary Heap

50+ Ternary Tree MCQs with FREE PDF

8. How many extra nodes are there in Full K-ary tree than complete K-ary tree?

a) 1

b) 2

c) 3

d) Both have same number of nodes

Answer: Both have same number of nodes

9. How many child nodes does each node of K-ary Tree contain?

a) 2

b) 3

c) more than k

d) at most k

Answer: at most k

10. Which of the following is the name of the node having child nodes?

a) Brother

b) Sister

c) Mother

d) Parent

Answer: Parent

11. What is the depth of the root node of K-ary tree?

a) 2

b) 1

c) 0

d) 3

Answer: 0

12. Can leaf node be called child node in a K-ary tree?

a) True

b) false

Answer: True

13. Can child node be always called Leaf node in the K-ary tree?

a) True

b) False

Answer: False

14. What is the upper bound for maximum leaves in K-ary tree with height h?

a) K*h

b) K^h

c) K+h

d) K-h

Answer: K^h

15. What is the height of a K-ary tree having only root node?

a) 1

b) 0

c) 2

d) 3

Answer: 0

50+ K-ary Tree MCQs with FREE PDF

16. Which type of tree does Van Emde Boas require to perform basic operations?

a) Unbalanced

b) Balanced

c) Complete

d) Non – Binary

Answer: Non – Binary

17. What is the time complexity for inserting a key or integer in Van Emde Boas data structure?

a) O (log M!)

b) O (M!)

c) O (M2)

d) O (log (log M))

Answer: O (log M!)

18. In which year was Van Emde Boas tree invented?

a) 1972

b) 1973

c) 1974

d) 1975

Answer: 1975

19. What is the time complexity for deleting a key or integer in Van Emde Boas data structure?

a) O (log M!)

b) O (log (log M))

c) O (M!)

d) O (M2)

Answer: O (log (log M))

20. What is the time complexity for finding a maximum and minimum integer in Van Emde Boas data structure?

a) O (log M!)

b) O (M!)

c) O (1)

d) O (log (log M))

Answer: O (1)

21. On which abstract data type does van Emde Boas tree performs the operation?

a) Tree

b) Linked List

c) Heap

d) Associative Array

Answer: Associative Array

22. Which operation find the value associated with a given key?

a) Insert

b) Find Next

c) Look up

d) Delete

Answer: Find Next

23. What is the other name or Van Emde Boas Tree data structure?

a) Van Emde Boas Array

b) Van Emde Boas Stack

c) Van Emde Boas Priority Queue

d) Van Emde Boas Heap

Answer: Van Emde Boas Priority Queue

50+ Van Emde Boas Tree MCQs with FREE PDF

24. What is the worst case efficiency for a path compression algorithm?

a) O(N)

b) O(log N)

c) O(N log N)

d) O(M log N)

Answer: O(M log N)

25. Path Compression algorithm performs in which of the following operations?

a) Create operation

b) Insert operation

c) Find operation

d) Delete operation

Answer: Find operation

26. What is the definition for Ackermann’s function?

a) A(1,i) = i+1 for i>=1

b) A(i,j) = i+j for i>=j

c) A(i,j) = i+j for i = j

d) A(1,i) = i+1 for i<1

Answer: A(1,i) = i+1 for i>=1

27. ___________ is one of the earliest forms of a self-adjustment strategy used in splay trees, skew heaps.

a) Union by rank

b) Equivalence function

c) Dynamic function

d) Path compression

Answer: Path compression

28. What is the depth of any tree if the union operation is performed by height?

a) O(N)

b) O(log N)

c) O(N log N)

d) O(M log N)

Answer: O(log N)

29. When executing a sequence of Unions, a node of rank r must have at least 2r descendants.

a) true

b) false

Answer: true

30. What is the value for the number of nodes of rank r?

a) N

b) N/2

c) N/2r

d) Nr

Answer: N/2r

31. What is the worst-case running time of unions done by size and path compression?

a) O(N)

b) O(logN)

c) O(N logN)

d) O(M logN)

Answer: O(M logN)

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32. What is the worst case time complexity of insertion operation(n =no. of candidates)?

a) O(1)

b) O(n)

c) O(log n)

d) O(n log n)

Answer: O(1)

33. What is computational geometry?

a) study of geometry using a computer

b) study of geometry

c) study of algorithms

d) study of algorithms related to geometry

Answer: study of algorithms related to geometry

34. What will be the time complexity of query operation if all the candidates are evenly spaced so that each bin has constant no. of candidates? (k = number of bins query rectangle intersects)

a) O(1)

b) O(k)

c) O(k2)

d) O(log k)

Answer: O(k)

35. What will be the time complexity of delete operation if all the candidates are evenly spaced so that each bin has constant no. of candidates? (m = number of bins intersecting candidate intersects)

a) O(1)

b) O(m)

c) O(m2)

d) O(log m)

Answer: O(m)

36. What will be the time complexity of insertion operation if all the candidates are evenly spaced so that each bin has constant no. of candidates? (m = number of bins intersecting candidate intersects)

a) O(1)

b) O(m)

c) O(m2)

d) O(log m)

Answer: O(m)

37. Efficiency of bin depends upon ___________

a) size of query and candidates

b) location of query and candidates

c) location and size of query and candidates

d) depends on the input

Answer: location and size of query and candidates

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38. In a k-d tree, k originally meant?

a) number of dimensions

b) size of tree

c) length of node

d) weight of node

Answer: number of dimensions

39. Each level in a k-d tree is made of?

a) dimension only

b) cutting and dimension

c) color code of node

d) size of the level

Answer: cutting and dimension

40. What is the worst case of finding the nearest neighbour?

a) O(N)

b) O(N log N)

c) O( log N)

d) O(N3)

Answer: O(N)

41. What is the run time of finding the nearest neighbour in a k-d tree?

a) O(2+ log N)

b) O( log N)

c) O(2d log N)

d) O( N log N)

Answer: O(2d log N)

42. How many prime concepts are available in nearest neighbour search in a kd tree?

a) 1

b) 2

c) 3

d) 4

Answer: 3

43. Reducing search space by eliminating irrelevant trees is known as?

a) pruning

b) partial results

c) freeing space

d) traversing

Answer: pruning

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44. In a k-d tree, k originally meant?

a) number of dimensions

b) size of tree

c) length of node

d) weight of node

Answer: number of dimensions

45. Each level in a k-d tree is made of?

a) dimension only

b) cutting and dimension

c) color code of node

d) size of the level

Answer: cutting and dimension

46. What is the worst case of finding the nearest neighbour?

a) O(N)

b) O(N log N)

c) O( log N)

d) O(N3)

Answer: O(N)

47. What is the run time of finding the nearest neighbour in a k-d tree?

a) O(2+ log N)

b) O( log N)

c) O(2d log N)

d) O( N log N)

Answer: O(2d log N)

48. How many prime concepts are available in nearest neighbour search in a kd tree?

a) 1

b) 2

c) 3

d) 4

Answer: 3

49. Reducing search space by eliminating irrelevant trees is known as?

a) pruning

b) partial results

c) freeing space

d) traversing

Answer: pruning

50. Several kinds of queries are possible on a k-d called as?

a) partial queries

b) range queries

c) neighbour queries

d) search queries

Answer: range queries

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Trees (Data Structure) MCQs PDF Download

1000+ Data Structure MCQs

Abstract Data Types
Application of Stacks
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Binary Trees
B Trees
Trees
Heap
Trie
Hash Tables
Graph

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