1. In what time can a 2-d tree be constructed?
a) O(N)
b) O(N log N)
c) O(N2)
d) O(M log N)
Answer: b
Explanation:
A perfectly balanced 2-d tree can be constructed in O(N log N) time. This value is computed mathematically.
2. Insertion into a 2-d tree is a trivial extension of insertion into a binary search tree.
a) true
b) false
Answer: a
Explanation:
Insertion of elements in a 2-d tree is similar to that of a binary search tree. Hence, it is a trivial extension of the binary search tree.
3. In a two-dimensional search tree, the root is arbitrarily chosen to be?
a) even
b) odd
c) depends on subtrees
d) 1
Answer: b
Explanation:
In a two- dimensional k-d tree (i.e.) 2-d tree, the root is arbitrarily chosen to be an odd level and it applies to all 2-d trees.
4. Which of the following is the simplest data structure that supports range searching?
a) Heaps
b) binary search trees
c) AA-trees
d) K-d trees
Answer: d
Explanation:
K-d trees are the simplest data structure that supports range searching and also it achieves the respectable running time.
5. 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: a
Explanation:
Initially, 2-d trees were created. Then, 3-d trees, 4-trees etc., where k meant the number of dimensions.
6. 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: b
Explanation:
Each level in a k-d tree is made of dimensions and cutting. Cutting and dimensions are used for insertion, deletion and searching purposes.
7. 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: a
Explanation:
The worst case analysis of finding the nearest neighbour in a k-d tree is mathematically found to be O(N).
8. 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: c
Explanation:
The run time of finding the nearest neighbour in a kd tree is given as O(2d log N) where 2d is the time taken to search the neighbourhood.
9. How many prime concepts are available in nearest neighbour search in a kd tree?
a) 1
b) 2
c) 3
d) 4
Answer: c
Explanation:
Three important concepts are available in finding the nearest neighbour. They are partial results, pruning, traversal order.
10. Reducing search space by eliminating irrelevant trees is known as?
a) pruning
b) partial results
c) freeing space
d) traversing
Answer: a
Explanation:
Pruning is eliminating irrelevant trees. Partial results are keeping best results and updating. Traversal is visiting all the nodes of a tree.
11. 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: b
Explanation:
Several range queries are possible on a k-d tree. One of the range queries is known as a partial match query.
12. What is the time taken for a range query for a perfectly balanced tree?
a) O(N)
b) O(log N)
c) O(√N+M)
d) O(√N)
Answer: c
Explanation:
For a perfectly balanced k-d tree, the range query could take O(√N+M) in the worst case to report M matches.
13. The 2d search tree has the simple property that branching on odd levels is done with respect to the first key.
a) True
b) False
Answer: a
Explanation:
Branching on odd levels is done with respect to the first key and branching on even levels is done with respect to the second key in a 2-d tree.
14. Who invented k-d trees?
a) Arne Andersson
b) Jon Bentley
c) Jon Von Newmann
d) Rudolf Bayer
Answer: b
Explanation:
Jon Bentley found k-d trees. Rudolf Bayer found red black trees. Arne Andersson found AA- trees.
15. What is the condition for an equivalence relation if two cities are related within a country?
a) the two cities should have a one-way connection
b) the two cities should have a two-way connection
c) the two cities should be in different countries
d) no equivalence relation will exist between two cities
Answer: b
Explanation:
If the two towns are in the same country and have a two-way road connection between them, it satisfies equivalence property.
16. Reversal algorithm and juggling algorithm for array rotation have the same time complexity.
a) True
b) False
Answer: a
Explanation:
Time complexity of juggling algorithm is O(n) which like that of reversal algorithm. They also have the same space complexity
