GCSE2023-25-paper 1 revision

Multiple Choice

What is a pixel?

• Smallest element of the picture

• 1 or 0

• Colours on a screen

• The number of bits used to represent the colour

Multiple Choice

A bitmap image is made up of

• Pixels

• Colours

• Sounds

• Samples

Multiple Choice

Increasing the colour depth means…

• A bigger range of colours can be used for each pixel
• More pixels are in the image.
• More colours are in the image.
• Darker colours

Multiple Choice

Which is NOT an effect of increasing the resolution in an image?

• More colours can be displayed.
• More binary will be required to create the image.
• Larger file size
• Higher quality image

Multiple Choice

Which is NOT an effect of increasing the colour depth in an image?

• More colours can be displayed.
• More binary will be needed per pixel to create the image.
• Larger file size
• More pixels will be displayed in the image.

Multiple Choice

Makes the file smaller by deleting parts of the file permanently (forever)

• Lossy Compression
• Lossless Compression

Multiple Choice

Makes the file smaller by giving repeated patterns/colours a specific code

• Lossy Compression
• Lossless Compression

Multiple Choice

Which of the following would not be suitable for Lossy Compression?

• Images

• Music

• Videos

• Text

Multiple Choice

Compression in general makes it _______ to send, upload and stream data

• Quicker

• Slower

Multiple Choice

Lossless compression permanently deletes the data

• True

• False

Multiple Choice

Lossy compression would be suitable for text files

• True

• False

Multiple Choice

Sound outside of computers is...

• Analogue

• Digital

Multiple Choice

In order for sound to be stored in a computer it must be converted to...

• Analogue

• Digital

• Buddhism

• JPEG

Multiple Choice

When recording sound, the number of samples recorded per second is called the:

• sample rate

• sample resolution

• colour depth

• File size

Multiple Select

Increasing the sample rate of a recording will result in...

• Higher-quality sound recording

• Increased file size

• Better compression

• Higher colour depth

• Increased amplitude

Multiple Choice

What is amplitude?

• Number of samples taken

• The number of bits per sample

• The height of the sound wave

• The pitch

Multiple Choice

The number of bits used to store each sound sample.

• Bit depth

• Bit rate

• Bit number

• Sound bits

Decomposition means breaking down into smaller parts.
The decomposed parts of a problem can be tackled independently and treated as smaller problems.

The decomposed parts of a solution can be created or coded separately, then brought back together.

​Decomposition and abstraction

Decomposition means breaking down into smaller parts.
The decomposed parts of a problem can be tackled independently and treated as smaller problems.

The decomposed parts of a solution can be created or coded separately, then brought back together.

Decomposition

Abstraction in computer science is the process of reducing complexity by focusing on the main idea and hiding the unnecessary details. It involves identifying the critical components and ignoring the irrelevant ones to simplify the design and use of complex systems.

Abstraction

Abstraction in computer science is the process of reducing complexity by focusing on the main idea and hiding the unnecessary details. It involves identifying the critical components and ignoring the irrelevant ones to simplify the design and use of complex systems.

Abstraction

You think of your smartphone as a device that can make calls, send messages, and browse the internet. You don't need to worry about how it works inside, you just use the apps and features.

When you use a specific app, like a messaging app, you interact with its interface: typing messages, sending emojis, and receiving notifications. You don't need to understand how the app processes your messages or how it connects to the internet

Coffee machines-

Programming examples:
Inbuilt subroutines or classes.

Examples of abstractions

Linear search

Data set-Marks [34, 7, 23, 32, 5, 62, 14, 18, 29, 41]

Best case- The target element is the first element in the list. O(1) (constant time)
Average case- The target element is somewhere in the middle of the list.
Worst case- The target element is the last element in the list or is not present in the list O(n).

Multiple Choice

Which type of lists or data sets are linear searching algorithms used for?

• Unsorted lists or data sets
• Sorted lists or data sets

Multiple Choice

Where can Linear Search be performed?

• On letters
• On numbers
• Both
• None of these

Multiple Choice

How many linear searches will it take to find the value 7 in the list [1,4,8,7,10,28]?

• 2
• 3
• 4
• 5

​Bubble sort

Sorting order- Ascending or Descending
Steps:
1. Begin at the first element of the list.
2. Compare the current element with the next element in the list.
3. If the current element is greater than the next element, swap them.
4. Move to the next pair of adjacent elements and repeat the comparison and swap steps.
5. Repeat for each pass when reaching the end.
6 When a Pass is made without any swap then list has been sorted (Final pass).

​Bubble sort example

Numbers= [34, 7, 23, 32, 5, 62, 14, 18, 29, 41].
How many maximum passes would it take to sort this list using bubble sort?
How many swaps would take place in first pass?
What is outcome of the first pass?
How many swaps would take place in the final pass?

​Bubble sort algorithm

def bubble_sort(data):

n = len(data)

pass_count = 0 # To count the number of passes

for i in range(n):

swapped = False

for j in range(0, n - i - 1):

if data[j] > data[j + 1]:

data[j], data[j + 1] = data[j + 1], data[j]

swapped = True

pass_count += 1

if not swapped:

break

return data, pass_count

# Dataset

data = [34, 7, 23, 32, 5, 62, 14, 18, 29, 41]

# Perform bubble sort

sorted_data, passes = bubble_sort(data)

print(f"Sorted Data: {sorted_data}")

print(f"Number of Passes: {passes}")

Logic gates

Multiple Choice

Which logic gate is shown here?

• OR

• NOT

• AND

• NAND

Multiple Choice

What would the ouput(z) be if the inputs were the following?

A=1

B=0

• 0

• 1

Multiple Choice

Which logic gate is shown here?

• AND

• OR

• XOR

• NAND

Multiple Choice

What would the output (z) be if the inputs were the following?

A=1

B=0

• 0

• 1

Multiple Choice

Which logic gate is associated with the  truth table?

• NAND

• OR

• NOT

• AND

Multiple Choice

Which logic gate is represented by the following symbol, ¬ ?

• AND

• OR

• NOT

• NAND

Multiple Choice

What is this logic gate?

• AND

• OR

• NAND

• NOR

• XOR

Data representation

Binary shifting left

Shifts the bits to the left by n positions. Equivalent to multiplying x by 2^n
Explanation: 5 in binary is 101. Left shifting 101 by 2 positions gives 10100, which is 20 in decimal.

Binary shifting Right

Shifts the bits to the right by n positions. Equivalent to dividing the x by 2^n
Explanation: 20 in binary is 10100. Right shifting 10100 by 2 positions gives 101, which is 5 in decimal.

Multiple Choice

What effect does a left shift of 2 places have in binary?

• Multiplies by 2

• Multiplies by 4

• Divides by 2

• Divides by 2

Multiple Choice

What effect does a right shift of 4 places have in binary?

• Divides by 8

• divides by 4

• Divides by 32

• Divides by 16

Multiple Choice

Add binary numbers shown?

• 01011010
• 10011010
• 10010101
• 10100010

Multiple Choice

00010111 + 01001100 =

• 1100011
• 11100011
• 1110001
• 1111011

Multiple Choice

What is this an example of?

• Overflow error
• 8 bit binary addition