FUNDAMENTAL PRINCIPLES AND CONCEPTS OF COMPUTING

Question 1

Set of well-defined instructions for performing a task or solving a problem.

Answer 1

ALGORITHM

Question 2

Each step is clearly defined.

Answer 2

PRECISION

Question 3

An algorithm must terminate after a finite number of steps.

Answer 3

FINITENESS

Question 4

Algorithms take input and produce output.

Answer 4

INPUT AND OUTPUT

Question 5

Each operation is basic enough to be carried out, in principle, by a human using only paper and pencil.

Answer 5

EFFECTIVENESS

Question 6

Uses divide-and-conquer to sort elements by partitioning arrays.

Answer 6

QUICKSORT

Question 7

Divides the list into halves, sorts them, and merges them.

Answer 7

MERGESORT

Question 8

Efficiently finds an element in a sorted list by repeatedly dividing the search interval in half.

Answer 8

BINARY SEARCH

Question 9

Checks each element in a list until the target is found.

Answer 9

LINEAR SEARCH

Question 10

Specialized formats for organizing, processing, retrieving, and storing data.

Answer 10

DATA STRUCTURES

Question 11

Store elements of the same type in contiguous memory locations.

Answer 11

ARRAY—>FIXED SIZE

Question 12

Each element points to the next.

Answer 12

LINKED LISTS—>SINGLY LINKED LIST

Question 13

Each element has pointers to both the next and previous elements.

Answer 13

LINKED LISTS—>DOUBLY LINKED LIST

Question 14

Elements are added and removed from the same end.

Answer 14

STACKS—>LIFO (Last In, First Out)

Question 15

Elements are added at one end and removed from the other.

Answer 15

QUEUES—>FIFO (First In, First Out)

Question 16

Each node has at most two children.

Answer 16

TREES—>BINARY TREE

Question 17

A binary tree where the left child is less than the parent node and the right child is greater.

Answer 17

TREES—>BINARY SEARCH TREE

Question 18

Consist of nodes (vertices) and edges (links).

Answer 18

GRAPHS—>DIRECTED/UNDIRECTED

Question 19

Provide fast access to data.

Answer 19

HASH TABLES—>KAY-VALUE PAIRS

Question 20

The study of the amount of resources required by an algorithm to run, typically time and space.

Answer 20

COMPUTATIONAL COMPLEXITY

Question 21

Describes the upper bound of an algorithm’s running time.

Answer 21

BIG O NOTATION

Question 22

Constant time, regardless of input size.

Answer 22

O(1)

Question 23

Linear time, grows proportionally with input size.

Answer 23

O(n)

Question 24

Logarithmic time, increases slowly with input size.

Answer 24

O(log n)

Question 25

Quadratic time, common in simple sorting algorithms like bubble sort.

Answer 25

O(n^2)

Question 26

Helps in selecting the most efficient algorithm for the problem and dataset size.

Answer 26

EFFICIENCY

Question 27

Predicts how an algorithm performs as data scales.

Answer 27

SCALABILITY

Question 28

Breaking complex problems into simpler sub-problems.

Answer 28

DECOMPOSITION

Question 29

Focusing on the essential details while ignoring the irrelevant ones.

Answer 29

ABSTRACTION

Question 30

Identifying patterns to simplify complex problems.

Answer 30

PATTERN RECOGNITION

Question 31

Simulations, data analysis, and modeling complex systems.

Answer 31

SCIENCE AND ENGINEERING

Question 32

Data processing, forecasting, and optimizing operations.

Answer 32

BUSINESS AND FINANCE

Question 33

Analyzing medical data, supporting diagnostic tools, and improving patient care.

Answer 33

HEALTHCARE

Question 34

Game development, animation, and virtual reality.

Answer 34

ENTERTAINMENT