2.1 Algorithms

Question 1

Principles of Computational Thinking

Answer 1

• Abstraction
• Decomposition
• Algorithmic thinking

Question 2

Abstraction

Answer 2

The process of removing all unnecessary details and including only the most relevant details.

Question 3

Decomposition

Answer 3

Breaking down a complex problem into smaller, more manageable parts.

Question 4

Algorithmic thinking

Answer 4

A way of getting to a solution by identifying the individual steps needed.

Question 5

Inputs

Answer 5

Anything that needs to be supplied to the program to meet its goals.

Question 6

Processes

Answer 6

Which calculations must be performed while the program is running.

Question 7

Outputs

Answer 7

What your program needs to output.

Question 8

Types of Errors

Answer 8

• Syntax errors
• Logic errors

Question 9

Syntax Errors

Answer 9

Errors that break the grammatical rules of a programming language and stop it from running.

Question 10

Logic Errors

Answer 10

Errors that produce an unexpected output, however the program still runs.

Question 11

Structure Diagrams

Answer 11

Help to illustrate problem decomposition. They use ‘Step Wise Refinement’
Each node should achieve a single task which can then be coded as a subprogram

Question 12

Trace Tables

Answer 12

Take each line at a time and write out the state of each variable.

Question 13

Flow Charts

Answer 13

A method of representing the sequence of steps in an algorithm in the form of a diagram.

Question 14

→

Answer 14

Represents flow from one component to the next.

Question 15

▭

Answer 15

Process
E.g. Input

Question 16

▱

Answer 16

Input/output

Question 17

◧◨

Answer 17

Subroutine

Question 18

⍚

Answer 18

Decision
E.g. IF/ELSE

Question 19

▢

Answer 19

Start/stop. Terminator.

Question 20

Types of Searches

Answer 20

• Binary search
• Linear search

Question 21

Binary Search

Answer 21

1. Calculate the midpoint of data set.
2. Check if that is the desired item
   IF desired item is lower than midpoint…
3. Repeat on left half data set
   IF desired item is higher than midpoint…
4. Repeat on right side of data set
5. Repeat until item is found.

Question 22

Characteristics of Binary Search

Answer 22

• Required data set to be ordered
• More efficient than linear search

Question 23

Linear Search

Answer 23

Starting from the beginning of a data set, each item is checked against to see if it is the desired item.

Question 24

Characteristics of Linear Search

Answer 24

• Will work on any storage device
• Efficient for smaller data sets, not large ones.

Question 25

Types of Sorts

Answer 25

• Bubble sort
• Merge sort
• Insertion sort

Question 26

Bubble Sort

Answer 26

Compares each item with the next and swaps them if they are out of order.
Algorithm ends when there are no more swaps.

Question 27

Characteristics of Bubble sort

Answer 27

• Sorts an unordered list of items.
• Most inefficient
• Easy to implement
• Popular for small data sets

Question 28

Merge Sort

Answer 28

Divide and Conquer method.
Creates two or more identical sub-problems from the largest problem and solves them individually, then combines their solutions to solve the large problem.

Question 29

Characteristics of Merge Sort

Answer 29

• Very efficient
• Works well for large data sets

Question 30

Insertion Sort

Answer 30

Inserts each item into its correct position in a data set.

Question 31

Characteristics of Insertion Sort

Answer 31

• Useful for inserting items into an already sorted list.
• Good for small data sets
• Not good for large data sets

Question 32

Pseudocode

Answer 32

A simple way of describing a set of instructions in a manner that resembles a programming language.

Question 33

Advantages of Pseudocode

Answer 33

• Can be quickly and easily converted into an actual programming language.
• Easy to understand
• Changes to the design can be incorporated easily

Question 34

Disadvantages of Pseudocode

Answer 34

• Can be hard to see how a program flows
• Time consuming.