1.4.1 Flashcards

1
Q

What are the 5 primitive data types?

A
  • Real / Floating Point – Stores decimal numbers (3.141)
  • Character - A single letter, number or special character (‘H’)
  • String – A collection of characters (“Hello World”)
  • Boolean – TRUE or FALSE
  • Integer – A positive or negative whole number (24, -34)
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2
Q

What is casting?

A

The process of changing one data type into another.

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3
Q

What is a character set?

What are some examples?

A
  • Contains all the characters the computer can represent.
  • Each character is represented by a unique binary value.
  • Used to map binary values to characters.
  • Examples: UNICODE and ASCII
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4
Q

Describe the ASCII character set

A
  • ASCII is a character set which is a subset of UNICODE
  • Uses 7 bits, or 8 bits for extended ASCII
  • Fewer characters can be represented than UNICODE
  • Characters from different languages cannot be represented in ASCII
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5
Q

Describe the UNICODE character set

A
  • Each character is represented by 1-4 bytes.
  • It supports a very large number of characters
  • It is backwards compatible with ASCII
  • Text using UNICODE rather than ASCII would take up more storage (roughly 4 times more)
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6
Q

Left shift the following 8-bit number 3 places: 00111010

What mathematical operation is this equivalent to?

A

Remove the required number of bits from the left

Add the same number of zeros to the right

11010000

Equivalent to multiplying the number

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7
Q

Right shift the following 8-bit number 3 places: 00111010

What mathematical operation is this equivalent to?

A

Remove the required number of bits from the right

Add the same number of zeros to the left

00000111

Equivalent to dividing the number

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8
Q

Convert 177 to an unsigned 8-bit binary number

A

10110001

128+32+16+1 = 177

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9
Q

Convert the unsigned 8-bit binary number 10110010 to denary

A

128+32+16+2 = 178

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10
Q

Convert 188 to Hex

A

BC

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11
Q

Convert the hex FE to a denary number

A

11111110 = 254

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12
Q

Convery -49 to an 8-bit binary number using two’s complement

A

11001111

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13
Q

Convert 49 to an 8-bit binary number using two’s complement

A

00110001

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14
Q

Convert -49 to an 8-bit binary number using sign and magnitude

A

10110001

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15
Q

Add the following two binary numbers

01101010 + 00111111

A

10101001

Carries - 11111100

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16
Q

Subtract the following two binary numbers

00101111 - 00010111

A

00011000

An overflow should have occured

17
Q

Mask 11010101 using the AND mask 10101010

18
Q

Mask 11010101 using the OR mask 10101010

19
Q

Mask 11010101 using the XOR mask 10101010

20
Q

Normalise 0001011000 001100

A

0101100000 001010

(Remove the two extra bits from the front of the mantissa and reduce the exponent value by 2)

21
Q

Convert 5.25 to an 6-bit mantissa and 3-bit exponent

A

010101 011

22
Q

Convert -5.25 to an 6-bit mantissa and 3-bit exponent

A

101011 011

23
Q

**Convert 01110 0001 to floating point denary

24
Q

Convert 0.125 to an 6-bit mantissa and 3-bit exponent

A

010000 110

25
Convert **-0.125** to an 6-bit mantissa and 3-bit exponent
**100000 101** ## Footnote Remember to normalise
26
**Add** the following floating point binary numbers stored in the two's complement format. **0110 0010 and 0100 0011**
**0111 0011**
27
Why do we normalise floating point numbers?
Allows for more **accuracy/precision** from the given number of bits So that the representation of each binary value is unique
28
What impact does increasing the size of the exponent have?
Increasing the number of bits used for the exponent increases the size of the number that can be stored.
29
What impact does increasing the size of the mantissa have?
Increasing the number of bits used for the mantissa increases the precision of the number that can be stored.
30
**Subtract** the following floating point binary numbers stored in the two's complement format. 010010 0100 - 010010 0010
0110110 0011