# Suffix Tree Multiple Choice Questions and Answers (MCQs)

This set of Data Structures & Algorithms Multiple Choice Questions & Answers (MCQs) focuses on “Suffix Tree

1. What is a time complexity for finding all the maximal palindrome in a string?
A) Ɵ (n)
B) Ɵ (n!)
C) Ɵ (1)
D) O (log n!)

Explanation: A palindrome is a string that reads the same both forward and backward. The time complexity of checking whether a substring is present in a string of length n is discovered to be O. (n). Finding all of the maximal palindromes in a series takes a long time (n).

2. What is a time complexity for finding all the tandem repeats?
A) Ɵ (n)
B) Ɵ (n!)
C) Ɵ (1)
D) O (n log n + z)

Explanation: When the nucleotide pattern repeats more than once in DNA, tandem repeats form. The time complexity of checking whether a substring is present in a string of length n is discovered to be O. (n). Finding all the tandem repeats in a string has a time complexity of O (n log n + z).

3. What is a time complexity for finding the longest palindromic substring in a string by using the generalized suffix tree?
A) Linear Time
B) Exponential Time
C) Logarithmic Time
D) Cubic Time

Explanation: A palindrome is a string that is identical when read both forward and backward. The time complexity of using a generalised suffix tree to find the longest palindromic substring in a string is linear.

4. Which of the following algorithm of data compression uses a suffix tree?
A) Weiner’s algorithm
B) Farach’s algorithm
C) Lempel – Ziv – Welch’s algorithm
D) Alexander Morse’s algorithm

Explanation: Weiner first proposed the Suffix Tree definition in 1973. Ukkonen made the Suffix tree’s first online contribution. In 1997, Farach contributed the first suffix tree for all alphabets. A suffix tree is used in the Lempel – Ziv – Welch data compression algorithm.

5. Which of the following data clustering algorithm uses suffix tree in search engines?
A) Weiner’s algorithm
B) Farach’s algorithm
C) Lempel – Ziv – Welch’s algorithm
D) Suffix Tree Clustering

Explanation: Weiner first proposed the Suffix Tree definition in 1973. Suffix’s first online contribution came from Ukkonen. In 1997, Farach contributed the first suffix tree for all alphabets. In search engines, Suffix Tree Clustering is a data clustering algorithm that employs the suffix tree.

6. What is a time complexity for finding the total length of all string on all edges of a tree?
A) Ɵ (n)
B) Ɵ (n!)
C) Ɵ (1)
D) O (n2)

Explanation: The time complexity of checking whether a substring is present in a string of length n is discovered to be O. (n). Finding the total length of all strings on all edges of a tree has an O time complexity (n2).

7. Can suffix tree be used in string problems occurring in a text editor.
A) True
B) False

Explanation: It’s a compact search tree or prefix tree in which the text location is represented by the suffix of text values in the keys. As a result, the suffix tree can be used to solve string problems in a text editor. The length of the string determines how long it takes to solve the problem.

8. Can suffix tree be used in bioinformatics problems and solutions.
A) True
B) False

Explanation: It’s a compact search tree or prefix tree in which the text location is represented by the suffix of text values in the keys. As a result, a suffix tree is used to solve bioinformatics problems such as pattern searching in DNA and protein sequences.

9. For what size of nodes, the worst case of usage of space in suffix tree seen?
A) n Nodes
B) 2n Nodes
C) 2n nodes
D) n! nodes

Explanation: The worst case of space use in a suffix tree, according to computer science, is for a Fibonacci term with 2n nodes. The time complexity of using space has been determined to be O. (n).

10. What is a time complexity for inserting an alphabet in the tree using hash maps?
A) O (log n!)
B) O (n!)
C) O (n2)
D) O (1)

Explanation: The suffix tree is sometimes referred to as the PAT tree or the place tree. It allows for fast string manipulation. The time it takes to create a suffix tree is proportional to its length. When using hash maps to insert an alphabet into a tree, the time complexity is constant, O (1).

11. What is a time complexity for x pattern occurrence of length n?
A) O (log n!)
B) Ɵ (n!)
C) O (n2)
D) Ɵ (n + x)
Explanation: The suffix tree is sometimes referred to as the PAT tree or the place tree. It allows for fast string manipulation. The time complexity of checking whether a substring is present in a string of length n is discovered to be O. (n). The time complexity of an event of x pattern of length n is (n + x).

12. What is a time complexity for finding the longest substring that is common in string S1 and S2 (n1 and n2 are the string lengths of strings s1, s2 respectively)?
A) O (log n!)
B) Ɵ (n!)
C) O (n2+ n1)
D) Ɵ (n1 + n2)

Explanation: The Suffix Tree allows for fast string manipulation. The time complexity of checking whether a substring is present in a string of length n is discovered to be O. (n). (n1 + n2) is the time complexity of finding the longest common substring in strings S1 and S2.

13. What is a time complexity for finding the longest substring that is repeated in a string?
A) O (log n!)
B) Ɵ (n!)
C) O (n2+ n1)
D) Ɵ (n)

Explanation: The Suffix Tree allows for fast string manipulation. The time complexity of checking whether a substring is present in a string of length n is discovered to be O. (n). Finding the longest substring that is repeated in a series has a time complexity of (n).

14. What is a time complexity for finding frequently occurring of a substring of minimum length in a string?
A) Ɵ (n)
B) Ɵ (n!)
C) O (n2+ n1)
D) O (log n!)

Explanation: The Suffix Tree allows for fast string manipulation. The time complexity of checking whether a substring is present in a string of length n is discovered to be O. (n). The time complexity of finding a substring of minimal length that occurs frequently in a string is (n).

15. What is a time complexity for finding the longest prefix that is common between suffix in a string?
A) Ɵ (n)
B) Ɵ (n!)
C) Ɵ (1)
D) O (log n!)

Explanation: The Suffix Tree allows for fast string manipulation. The time complexity of checking whether a substring is present in a string of length n is discovered to be O. (n). Finding the longest common prefix between two suffix in a string has a time complexity of (1).

16. Who proposed the concept of Suffix Tree?
A) Weiner
B) Samuel F. B. Morse
C) Friedrich Clemens Gerke
D) Alexander Morse

Explanation: A suffix tree is also known as a PAT tree or a place tree in computer science. It’s a compact search tree or prefix tree in which the text location is represented by the suffix of text values in the keys. Weiner first proposed the Suffix Tree definition in 1973.

17. Who among the following provided the first online contribution of Suffix Tree?
A) Weiner
B) Samuel F. B. Morse
C) Ukkonen
D) Alexander Morse

Explanation: A suffix tree is also known as a PAT tree or a place tree in computer science. Weiner first proposed the Suffix Tree definition in 1973. Ukkonen contributed the first online version of Suffix tree, which had the time complexity of the fastest algorithm at the time.

18. What is the time complexity of Uttkonen’s algorithm?
A) O (log n!)
B) O (n!)
C) O (n2)
D) O (n log n)

Explanation: Weiner first proposed the Suffix Tree definition in 1973. Ukkonen contributed the first online version of Suffix tree, which had the time complexity of the fastest algorithm at the time. The time complexity of Ukkonen’s algorithm was n log n.

19. Who among the following provided the first suffix tree contribution for all alphabet?
A) Weiner
B) Farach
C) Ukkonen
D) Alexander Morse
Explanation: Weiner first proposed the Suffix Tree definition in 1973. Ukkonen contributed the first online version of Suffix tree, which had the time complexity of the fastest algorithm at the time. In 1997, Farach contributed the first suffix tree for all alphabets.

20. Who among the following algorithm is used in external memory and compression of the suffix tree?
A) Weiner’s algorithm
B) Farach’s algorithm
C) Ukkonen’s algorithm
D) Alexander Morse

Explanation: Weiner first proposed the Suffix Tree definition in 1973. Ukkonen made the Suffix tree’s first online contribution. In 1997, Farach contributed the first suffix tree for all alphabets. In external memory and compression, Farach’s algorithm is used.

21. Which statement is correct of suffix tree with a string of length n?
A) The tree has n leaves.
B) The tree has n roots
C) Height of Tree is n
D) Depth of tree is n

Explanation: A suffix tree is also known as a PAT tree or a place tree in computer science. It’s a compact search tree or prefix tree in which the text location is represented by the suffix of text values in the keys. The suffix tree has leaves equal to n for a string of length n.

22. Do all the nodes have at least two children in suffix tree.
A) True
B) False

Explanation: It’s a compact search tree or prefix tree in which the text location is represented by the suffix of text values in the keys. Except for the root nodes, all internal nodes have at least two children.

23. Can the two edges that are coming out of a node have labels of string beginning with the same character?
A) True
B) False

Explanation: It’s a compact search tree or prefix tree in which the text location is represented by the suffix of text values in the keys. Except for the root nodes, all internal nodes have at least two children. No two edges that emerge from a node have string labels that start with the same character.

24. Which tree allows fast implementation of a set of string operation?
A) Rope Tree
B) Tango Tree
C) Generalized Suffix Tree
D) Top Tree

Explanation: The generalised suffix is a special suffix tree in computer science that includes a series of strings or words rather than a single string like the suffix tree. Consequently A generalised suffix tree may be used to perform various operations on a collection of strings.

25. What is a time complexity for checking a string of length n is substring or not?
A) O (log n!)
B) O (n!)
C) O (n2)
D) O (n)

Explanation: The suffix tree is sometimes referred to as the PAT tree or the place tree. It allows for fast string manipulation. The time it takes to create a suffix tree is proportional to its length. The time complexity of checking whether a substring is present in a string of length n is discovered to be O. (n).

26. What is the other name for Suffix Tree?
A) Array
B) Stack
C) Priority Queue
D) PAT Tree

Explanation: A suffix tree is also known as a PAT tree or a place tree in computer science. It’s a compact search tree or prefix tree in which the text location is represented by the suffix of text values in the keys.

27. Which tree allows fast implementation of string operation?
A) Rope Tree
B) Suffix Tree
C) Tango Tree
D) Top Tree

Explanation: A suffix tree is also known as a PAT tree or a place tree in computer science. It’s a compact search tree or prefix tree in which the text location is represented by the suffix of text values in the keys. It enables the user to perform fast string operations.

28. How much time does construction of suffix tree take?
A) O (log M)
B) O (M!)
C) Exponential to Length of Tree
D) Linear to Length of Tree

Explanation: The suffix tree is sometimes referred to as the PAT tree or the place tree. It’s a compact search tree or prefix tree in which the text location is represented by the suffix of text values in the keys. It allows for fast string manipulation. The time it takes to create a suffix tree is proportional to its length.

29. How much space does construction of suffix tree takes?
A) O (log M)
B) Exponential to Length of Tree
C) O (M!)
D) Linear to Length of Tree

Explanation: The suffix tree is sometimes referred to as the PAT tree or the place tree. It’s a compact search tree or prefix tree in which the text location is represented by the suffix of text values in the keys. It allows for fast string manipulation. The amount of space used to create a suffix tree is proportional to its length.

30. Which tree provides a linear time solution for substring operation?
A) Rope Tree
B) Suffix Tree
C) Tango Tree
D) Top Tree

Explanation: It’s a compact search tree or prefix tree in which the text location is represented by the suffix of text values in the keys. It enables the user to perform fast string operations. Suffix tree can perform the substring operation in linear time.

A suffix tree (also known as a PAT tree or, in an earlier form, a position tree) is a compact trie that contains all of the suffixes of a given text as keys and text positions as values. Many critical string operations can be implemented very quickly using suffix trees. The time and space required to create such a tree for the string displaystyle SS is linear in the duration of disparities in health SS. Several operations, such as locating a substring in social – economic SS, locating a substring if a certain number of mistakes are permitted, locating matches for a regular expression pattern, and so on, can be performed quickly once the structure is built.