1. Fundamentals of algorithms

Question 1

Computational Thinking

Answer 1

Solving problems using a computer system.

Question 2

Decomposition

Answer 2

Breaking down complex problems into smaller, more manageable parts.

Question 3

Abstraction

Answer 3

Focusing on essential details while ignoring unnecessary information.

Question 4

Algorithm

Answer 4

A set of step-by-step instructions designed to solve a specific problem.

Question 5

Systematic Approach

Answer 5

Taking a logical approach and using algorithmic thinking to solve a problem.

Question 6

Pseudocode

Answer 6

Text-based tool using short English statements to describe an algorithm.

Question 7

Program Code

Answer 7

Specific to a programming language, unlike generic pseudocode.

Question 8

Flowchart

Answer 8

Visual tool using shapes to represent different functions of an algorithm, showing input/output, processes, decisions, and control flow.

Question 9

Algorithm Inputs

Answer 9

Data or information entered into a program before processing, sourced from various inputs like user interaction or sensors.

Question 10

Algorithm Processes

Answer 10

Doing actions in the algorithm that transform inputs into desired outputs, executed by the CPU.

Question 11

Algorithm Outputs

Answer 11

Result of processing in an algorithm, often the indicator of whether the algorithm functions as intended.

Question 12

Trace Table

Answer 12

Tool used to trace through an algorithm or program, testing for logic errors and recording the state of the algorithm at each step.

Question 13

Purpose of Trace Table

Answer 13

Discovering the algorithm’s purpose, showing output data and intermediary steps, and recording the state of the algorithm.

Question 14

Trace Table with Algorithms

Answer 14

Trace tables can be used with flowcharts, pseudocode, or program code to analyze algorithms and programs.

Question 15

Algorithm Efficiency

Answer 15

Measure of the time taken to complete an algorithm.

Question 16

Linear Search

Answer 16

Sequentially checks each element in the list until the target value is found. A linear search starts with the first value in a dataset and checks every value one at a time until all values have been checked
A linear search can be performed even if the values are not in order.

Question 17

Binary Search

Answer 17

Divides the sorted list into halves, eliminating half of the remaining elements in each step until the target value is found. A binary search keeps halving a dataset by comparing the target value with the middle value, going left if smaller, right if bigger, until it finds the value or realises it’s not there
To perform a binary search the data must be in order! A binary search can be performed on datasets containing numbers or words. Searching for a word instead of a number is the same process, except comparisons are made based on position in the alphabet (alphabetically) instead of numerical size

Question 18

Algorithm Selection

Answer 18

Choosing the most appropriate algorithm based on factors like input size, data structure, and problem constraints.

Question 19

Searching algorithm

Answer 19

Searching algorithms are precise step-by-step instructions that a computer can follow to efficiently locate specific data in massive datasets.

Question 20

Linear Search advantages / disadvantages

Answer 20

Advantages:
Works on unsorted datasets. Faster (than binary) on very small datasets. Simple to understand and implement.
Disadvantages:
Slow for large datasets. Inefficient, starts at the beginning each time.

Question 21

Binary Search advantages / disadvantages

Answer 21

Advantages:
Fast for large datasets. Efficient for repeated searches.
Disadvantages:
Dataset must be in order. More complex to implement.

Question 22

Sorting Algorithm

Answer 22

Precise step-by-step instructions for efficiently sorting data in datasets.

Question 23

Merge Sort

Answer 23

Sorting algorithm using the ‘divide and conquer’ strategy to divide a dataset into smaller sub-datasets and merge them back together in the correct order. Merge sort divides the dataset into smaller parts, sorts each part separately, and then merges them back together to obtain the sorted dataset.

Question 24

Bubble Sort

Answer 24

Simple sorting algorithm that compares adjacent elements and swaps them if they are in the wrong order. Bubble sort checks values in pairs and swaps them if they are not in the correct order. Bubble sort continues until there are no more swaps needed, indicating the dataset is sorted.

Question 25

Merge Sort advantages / disadvantages

Answer 25

Advantages:
Suitable for large datasets
Performs well no matter how unorganized the data is
Disadvantages:
Uses a lot of memory
More complex to implement

Question 26

Bubble Sort advantages / disadvantages

Answer 26

Advantages:
Simple to understand and implement
Disadvantages:
Slow for large datasets
Inefficient, as it iterates through the data multiple times