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A Level Computer Science > 4.5 Fundamentals of Data Representation > Flashcards

4.5 Fundamentals of Data Representation Flashcards

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1
Q

Natural Numbers

A

All positive integers starting and including 0

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2
Q

Ordinal Numbers

A

Used to tell the position of a number that is placed in an order

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3
Q

Counting and Measurement

A

Counting = Natural Numbers
Measurement = Real Numbers

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4
Q

Hex vs Binary (3)

A
  • Hex is easier to code/read/enter/spot errors/remember
  • less change of human error
  • less digits in hex: 2 in hex vs 8 in binary
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5
Q

The Bit (definition)

A

The fundamental unit of information

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6
Q

n bits can represent – values

A

2^n

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7
Q

Prefixes

A
  • Powers of 10 prefixes:
    • Kilo, K - 10^3
    • Mega, M - 10^6
    • Giga, G - 10^9
    • Tera, T - 10^12
  • Powers of 2 prefixes:
    • Kibi, Ki - 2^10
    • Mebi, Mi - 2^20
    • Gibi, Gi - 2^30
    • Tebi, Ti - 2^40
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8
Q

Signed vs Unsigned Binary

A

Unsigned = cannot represent -ve numbers
Signed = range of magnitude decreases

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9
Q

Binary Subtraction (3)

A
  • Convert w/ 2’s complement (flip +1)
  • Add numbers together
  • Discard overflow
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10
Q

Decimal Numbers (2)

A
  • Not accurate - close as possible, not over
  • More bits available = greater precision
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11
Q

Error Calculations

A
  • Absolute error = original - binary
  • Relative error = absolute/original
  • Percentage error = relative x 100%
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12
Q

Normalised Binary (5)
- +ve starts with
- -ve start with
- Parts

A
  • +ve: start with 0.1
  • -ve: start with 1.0
  • Mantissa = main value
  • Exponent = power
    • Starts with 1 if -ve
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13
Q

Advantages of Normalised Binary (3)

A
  • Maximise precision
  • Better accuracy
  • Unique representation of each number (distinguish +ve and -ve)
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14
Q

Character Sets (2)

A
  • Every number, letter, symbol you can type has an ASCII code associated to it
  • Globally recognised, uniform
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15
Q

ASCII (3)

A
  • English alphabet
  • Lower, upper, nums, some symbols
  • 7 bits = 128 possibilities
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16
Q

Unicode (2)

A
  • ASCII + all alphabets, symbols, emojis
  • Use ASCII until character is only in Unicode
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17
Q

Parity Bit (3)

A
  • Bit added to end of string of binary
  • Ensures total num 1 bits is even/odd
  • Simplest form of error checking
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18
Q

Advantages of Parity Bits (3)

A
  • little storage
  • less to process
  • easy to make
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19
Q

Disadvantages of Parity Bits (3)

A
  • can’t detect multiple errors
  • doesn’t fix errors
  • not very reliable
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20
Q

Majority Voting (2)

A
  • Bits can change due to interference
  • Each bit transmitted x3 - most common chosen
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21
Q

Advantages of Majority Voting (4)

A
  • detects multiple errors
  • fixes errors
  • easier to make
  • very reliable
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22
Q

Disadvantages of Majority Voting (2)

A
  • more storage
  • more to process
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23
Q

Check Sums Process (5)

A
  • Data sent in block of several bytes
  • Bytes added up
  • Result transmitted with data
  • Receiver works out checksum
  • Data accepted if they match
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23
Q

Analog vs Digital

A

Analog = continuous stream of transmission
Digital = discrete set of fixed values

24
Q

Check Digit (5)
- Process
- Purpose

A
  • Many different algorithms used
  • Calculated from all other digits in code
  • Added to end
  • Compared when received
  • Purpose: spot human error of data entry
25
Q

Vector Images
- Process
- Examples

A
  • Objects layered + properties recorded
    • Size (width/height/radius), colour fill/outline, weight
  • e.g. Logos
26
Q

Advantages of Vector Images (4)

A
  • better quality
  • small file size
  • edit easily
  • scalable
27
Q

Disadvantages of Vector Images (2)

A
  • can’t represent real life images
  • can’t compress
28
Q

Bitmap Images (7)
- Process
- More bits =
- Resolution =
- Colour Depth =
- Metadata (2)
- Examples

A
  • Pixels with colour codes (in binary) stored in grid like pattern
  • More bits = more colours = better quality = larger file size
  • Resolution = num pixels per inch
  • Colour depth = num bits for each pixel to assign colour (n bits = 2n colours)
  • Metadata: data attached to an image
    • Width, height, colour depth, date, author, file type
  • e.g. photos, videos, digital art
29
Q

Advantages of Bitmap Images (1)

A
  • can represent real life images
30
Q

Disadvantages of Bitmap Images (4)

A
  • large file size
  • low quality
  • can’t edit easily
  • not scalable
31
Q

Sound (3)

A
  • Need analogue to digital converter
  • Samples taken by measuring amplitude of waves at regular intervals
  • Result stored in binary
32
Q

Sample Rate (definition)

A

Num samples per second

33
Q

Sample Resolution (definition)

A

num bits available for each sample

34
Q

The higher the sample resolution/rate (2)

A
  • the better the quality
  • the larger the file size
35
Q

Bit Rate (definition)

A

sample rate x resolution

36
Q

Nyquist Theorem (definition)

A

To produce an accurate reading: sample rate >/ 2x highest freq in original sound

37
Q

MIDI (8)

A
  • Technical standard
  • Describes: Protocol, digital interface, standard set of connectors
  • Allows for range of instruments/computers to communicate
  • Controller sends+receives event messages
    • Duration of note, pitch, vibrato
    • All easily changed
  • No live audio - pre recordings of real instruments
  • “List of instructions”
38
Q

Advantages of MIDI (6)

A
  • Easy modify/edit
  • Score directly generated
  • No data lost about notes
  • Easy change instruments
  • No background noise
  • Smaller file sizes
39
Q

Advantages of Lossless Compression (2)

A
  • can be used on anything
  • original data can be retrieved (quality not lost)
40
Q

Disadvantages of Lossless Compression (2)

A
  • smaller reduction
  • slower transfer
41
Q

Advantages of Lossy Compression (2)

A
  • larger reduction
  • faster transfer
42
Q

Disadvantages of Lossy Compression (2)

A
  • can’t use on text files/programs
  • original data cannot be retrieved
43
Q

Run Length Encoding (4)
- Type of compression
- Process
- Used On

A
  • Lossless compression
  • Identifies repeating patterns
  • Stores one copy of pattern + how many times repeats in succession
  • Used on: images, sound, text (unlikely)
43
Q

Dictionary Encoding (5)
- Type of compression
- Process

A
  • Lossless compression
  • Long passages with lots repeated words
  • Variable length of strings of symbols of original data represented by single tokens
  • Dictionary formed using token as index
  • Strings of symbols used as entries
44
Q

Encryption (definition)

A

act of protecting data by making it unreadable

45
Q

Caesar Cipher

A

shift right n places

46
Q

Advantages of Caesar Cipher (2)

A
  • easier to code
  • easier to generate key
47
Q

Disadvantages of Caesar Cipher (4)

A
  • easy to hack
  • 25 possible keys
  • less secure
  • key must be kept secure
48
Q

Vernam Cipher (9)
- Process
- Key must be
- Features

A
  • Plaintext XOR key = ciphertext
  • Ciphertext XOR key = plaintext
  • Key must be:
    • Same length
    • Completely random
    • Only used once
    • Kept secure
  • Mathematically impossible to hack
    • nothing can be learnt about plaintext from ciphertext
49
Q

Advantages of Vernam Cipher (2)

A
  • mathematically secure
  • larger range of keys
50
Q

Disadvantages of Vernam Cipher (3)

A
  • harder to code
  • harder to generate keys
  • key must be kept secure
50
Q

Digital Signature (4)
- Features
- Reasons

A
  • Similar to real life signature
  • Uses mathematical functions, private, public keys to create unique signature
  • Reasons
    • Know if message corrupted
    • Sender verification
50
Q

Process of Sending a Message Using Digital Signatures

A
  • Hash plaintext → message digest
  • Sender’s private + digest → signature
  • Add signature to plaintext
  • Encrypt (sign + pt) w/ receiver’s public
  • Send message
  • Decrypt (sign + pt) w/ receiver’s private
  • Split signature and plaintext
  • Sender’s public + signature → digest
  • Rehash plaintext → message digest
  • Compare digests
51
Q

Underflow (definition)

A

Storing less bits in a given space
e.g. storing 3 bits as a nibble: 0011, 00 is the underflow

52
Q

Why Normalise Floating Point (2)

A
  • better accuracy for a given number of bits
  • unique representation for all numbers (can tell easily if +ve or -ve)
53
Q

Floating Point vs Fixed Point

A
  • Floating: far greater range of values for a given amount of bits
  • Floating: can take bits from exponent to add to mantissa to improve accuracy
  • Fixed: greater precision for a given amount of bits (more accurate)
54
Q

Mantissa =
Exponent =

A

Mantissa = Accuracy
Exponent = Range

55
Q

Bytecode

A
  • what is produced by a compiler
  • intermediatory code
  • not processor specific
  • executable files are processor specific
  • can convert into different processor specific executable files
  • use a virtual machine to run security checks
  • bytecode can be altered to be specific for a virtual machine

A Level Computer Science (13 decks)

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