Algorithm Efficiency: Master Algorithm Performance Analysis

Question 1

Which of the following is NOT a valid metric for measuring algorithm efficiency?

Accepted Answer

Ease of implementation

Answer

Time complexity

Answer

Auxiliary space

Answer

Number of comparisons

Question 2

Which of the following techniques can be employed to enhance algorithm efficiency?

Accepted Answer

Memoization

Answer

Recursion

Answer

Brute force

Answer

Infinite loops

Question 3

An algorithm with an auxiliary space of Ο(n) requires:

Accepted Answer

Linear extra space

Answer

Constant extra space

Answer

Quadratic extra space

Answer

Exponential extra space

Question 4

What is a key benefit of employing dynamic programming to enhance algorithm efficiency?

Accepted Answer

Elimination of redundant computations

Answer

Increased code complexity

Answer

Removal of recursion

Answer

Improved worst-case time complexity

Question 5

The insertion sort algorithm has a time complexity of:

Accepted Answer

Ο(n²)

Answer

Ο(n)

Answer

Ο(n log n)

Answer

Ο(n³)

Question 6

Which of the following is a potential drawback of using memoization to improve algorithm efficiency?

Accepted Answer

Increased memory utilization

Answer

Enhanced code readability

Answer

Elimination of recursive calls

Answer

Improved worst-case time complexity

Question 7

The time complexity of the binary search algorithm is:

Accepted Answer

Ο(log n)

Answer

Ο(1)

Answer

Ο(n)

Answer

Ο(n²)

Question 8

An algorithm with a time complexity of O(n^2) performs how many operations for an input of size n?

Accepted Answer

n^2

Answer

n

Answer

n*log(n)

Answer

log(n)

Question 9

Which of the following sorting algorithms has an average-case time complexity of O(n*log(n))?

Accepted Answer

Merge sort

Answer

Bubble sort

Answer

Selection sort

Answer

Quicksort

Question 10

What is the main purpose of using a binary search algorithm?

Accepted Answer

To search for an element in a sorted array

Answer

To search for an element in an unsorted array

Answer

To sort an array in ascending order

Answer

To find the maximum element in an array

Question 11

An algorithm with a space complexity of O(n) requires how much memory for an input of size n?

Accepted Answer

n units

Answer

n^2 units

Answer

log(n) units

Answer

constant units

Question 12

Which data structure is most suitable for implementing a priority queue?

Accepted Answer

Heap

Answer

Array

Answer

Linked list

Answer

Binary search tree

Question 13

What is the difference between asymptotic analysis and exact analysis of algorithms?

Accepted Answer

Asymptotic analysis provides an approximation of algorithm efficiency, while exact analysis is precise

Answer

Exact analysis provides an approximation of algorithm efficiency, while asymptotic analysis is precise

Answer

Asymptotic analysis considers the best-case scenarios, while exact analysis considers all possible inputs

Answer

There is no difference between asymptotic analysis and exact analysis

Question 14

What does the big-O notation in algorithm analysis signify?

Accepted Answer

It provides an upper bound on the algorithm's worst-case performance

Answer

It represents the exact number of operations performed by the algorithm

Answer

It indicates the average-case performance of the algorithm

Answer

It is only used for sorting algorithms

Question 15

Which technique can improve the efficiency of searching a sorted array?

Accepted Answer

Binary Search

Answer

Linear Search

Answer

Recursion

Answer

Selection Sort

Question 16

Which of the following is NOT a potential benefit of using an optimized algorithm?

Accepted Answer

Improved code readability

Answer

Faster execution time

Answer

Reduced memory usage

Answer

Increased algorithm robustness

Question 17

Which of the following data structures is commonly used for implementing a queue?

Accepted Answer

Linked List

Answer

Array

Answer

Binary Search Tree

Answer

Hash Table

Question 18

What is a potential disadvantage of using a recursive algorithm?

Accepted Answer

Increased memory usage

Answer

Reduced code efficiency

Answer

Unpredictable behavior

Answer

Limited problem size

Question 19

True or False: Big-O notation provides an upper bound on the number of operations performed by an algorithm in the worst case.

Accepted Answer

True

Answer

False

Question 20

An algorithm with a time complexity of O(n²) is said to be:

Accepted Answer

Polynomial time

Answer

Exponential time

Answer

Constant time

Answer

Logarithmic time

Question 21

What is the space complexity of an algorithm that stores all input values in a list?

Accepted Answer

O(n)

Answer

O(1)

Answer

O(log n)

Answer

O(n²)

Question 22

An algorithm that processes each element in an array of size n has a time complexity of:

Accepted Answer

O(n)

Answer

O(1)

Answer

O(log n)

Answer

O(n²)

Question 23

What is the time complexity of a recursive algorithm that divides the problem size by 2 in each step?

Accepted Answer

O(log n)

Answer

O(1)

Answer

O(n)

Answer

O(n²)

Question 24

An algorithm with a time complexity of O(n log n) is considered to be:

Accepted Answer

Polynomial time

Answer

Exponential time

Answer

Logarithmic time

Answer

Constant time

Question 25

In algorithm design, why is it crucial to consider both time and space complexity?

Accepted Answer

Balancing time and space complexity optimizes resource usage and enhances algorithm performance.

Answer

Prioritizing time complexity is usually more important than optimizing space complexity.

Answer

Trading off space complexity for time complexity is always advantageous for algorithm efficiency.

Answer

Space complexity is irrelevant when analyzing algorithm efficiency.

Question 26

Which of the following is NOT a typical measure of algorithm efficiency?

Accepted Answer

Accuracy

Answer

Space complexity

Answer

Time complexity

Answer

Memory usage

Question 27

Which of the following sorting algorithms has the best worst-case time complexity?

Accepted Answer

Merge Sort

Answer

Insertion Sort

Answer

Bubble Sort

Answer

Quick Sort

Question 28

An algorithm that utilizes a stack data structure typically has O(1) complexity for:

Accepted Answer

Push and pop operations.

Answer

Search operations

Answer

Insert operations

Answer

Delete operations

Question 29

Which of the following is a viable approach to enhance the efficiency of an algorithm?

Accepted Answer

Reducing the number of iterations.

Answer

Ignoring edge cases

Answer

Using more complex data structures

Answer

Increasing the memory usage

Question 30

An algorithm with space complexity O(n) requires how much additional memory for every additional input element?

Accepted Answer

An amount proportional to the input size

Answer

A logarithmic amount

Answer

A quadratic amount

Answer

A fixed amount

Question 31

Which of the following is a common technique for reducing the time complexity of a recursive algorithm?

Accepted Answer

Memoization

Answer

Branch and bound

Answer

Dynamic programming

Answer

Parallel processing

Question 32

Which of the following is a trade-off to consider when optimizing algorithm efficiency?

Accepted Answer

Space versus time

Answer

Simplicity versus accuracy

Answer

Readability versus maintainability

Answer

Cost versus benefit

Question 33

Which of the following time complexities represents the best-case scenario for a linear search algorithm?

Accepted Answer

O(1)

Answer

O(n^2)

Answer

O(log n)

Answer

O(n)

Question 34

Consider the function f(n) = 2n^2 + 5n + 3. What is the Big-O notation for this function?

Accepted Answer

O(n^2)

Answer

O(log n)

Answer

O(n)

Answer

O(1)

Question 35

Which of the following sorting algorithms has a worst-case time complexity of O(n log n)?

Accepted Answer

Merge Sort

Answer

Bubble Sort

Answer

Insertion Sort

Answer

Selection Sort

Question 36

Which of the following is NOT a common algorithm efficiency measure?

Accepted Answer

Battery life

Answer

Time complexity

Answer

Input size

Answer

Space complexity

Question 37

An algorithm with O(n^2) time complexity is considered:

Accepted Answer

Quadratic

Answer

Logarithmic

Answer

Linear

Answer

Constant

Question 38

Which sorting algorithm has an average time complexity of O(n log n)?

Accepted Answer

Merge Sort

Answer

Insertion Sort

Answer

Selection Sort

Answer

Bubble Sort

Question 39

What is the primary difference between asymptotic and exact analysis of algorithm efficiency?

Accepted Answer

Asymptotic analysis ignores constants and low-order terms, while exact analysis considers them.

Answer

Asymptotic analysis is more accurate than exact analysis.

Answer

Exact analysis is only useful for small datasets.

Question 40

Which of the following is a technique to improve algorithm efficiency?

Accepted Answer

Memoization

Answer

Adding redundant code

Answer

Increasing the input size

Answer

Using a less efficient data structure

Question 41

Which of the following algorithms has the worst-case time complexity of O(2^n)?

Accepted Answer

Exponential Search

Answer

Dijkstra's Algorithm

Answer

Binary Search

Answer

Breadth-First Search

Question 42

An algorithm takes a constant amount of time to execute, irrespective of the input size. What is its Big-O time complexity?

Accepted Answer

O(1)

Answer

O(log n)

Answer

O(n)

Answer

O(n^2)

Question 43

Which of the following algorithms has exponential time complexity?

Accepted Answer

Recursive Fibonacci calculation

Answer

Linear search

Answer

Merge sort

Answer

Binary tree traversal

Question 44

Which algorithm has time complexity of O(n), where n is the number of elements in the input?

Accepted Answer

Linear search

Answer

Selection sort

Answer

Merge sort

Answer

Quick sort

Question 45

Which algorithm is particularly effective for sorting nearly sorted arrays?

Accepted Answer

Insertion sort

Answer

Selection sort

Answer

Merge sort

Answer

Bubble sort

Question 46

Which technique can be used to enhance algorithm efficiency by storing previously computed results?

Accepted Answer

Memoization

Answer

Greedy algorithms

Answer

Recursion

Answer

Dynamic programming

Question 47

What is the worst-case time complexity of Merge sort?

Accepted Answer

O(n log n)

Answer

O(n^2)

Answer

O(1)

Answer

O(n)

Question 48

What is the average-case time complexity of Bubble Sort?

Accepted Answer

O(n^2)

Answer

O(n)

Answer

O(n log n)

Answer

O(1)

Question 49

Which of the following is a common approach to measuring algorithm efficiency?

Accepted Answer

Big O Notation

Answer

Theta Notation

Answer

Little o Notation

Answer

Omega Notation

Question 50

What is the best time complexity that can be achieved by any sorting algorithm?

Accepted Answer

O(n log n)

Answer

O(n)

Answer

O(1)

Answer

O(n^2)