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2210 · 0478Paper 1 · Computer Systems§1.1, §1.2, §1.3

1. Data Representation

Everything is numbers. Learn how binary, hexadecimal, text, images and sound are stored and how data is compressed.

Statometer95BankerNext Paper 194%
Marks a paper21.1 · 28%Rank#3 of 10 · #2 on P1Trend · last 12Oct/Nov 24 · 13: 39 marksFeb/Mar 25 · 12: 28 marksMay/Jun 25 · 11: 26 marksMay/Jun 25 · 12: 22 marksMay/Jun 25 · 13: 12 marksOct/Nov 25 · 11: 34 marksOct/Nov 25 · 12: 20 marksOct/Nov 25 · 13: 7 marksFeb/Mar 26 · 12: 10 marksMay/Jun 26 · 11: 22 marksMay/Jun 26 · 12: 38 marksMay/Jun 26 · 13: 22 marks
9 in 10 chance in the next paper

Everything for this topic — study hub

O Level / IGCSE · 2210 · 0478 · Paper 1

Statometer — what 25 real papers say about this topic and each of its 4 syllabus bullets

Banker · #3 of 10 in O Level / IGCSE · recomputed with every new session

95BANKER
Banker#3 of 10 in O Level / IGCSE#2 on Paper 1 Steady

Set in nearly every paper and worth a big slice of it — revise first, expect it.

Next Paper 1
94%
9 in 10 chance it is set
Marks a paper
21.1 / 75
28% of Paper 1 · fair share 17%
Appeared in
25 / 25
Paper 1 sittings 20232026
Last set
May/Jun 2026
0478/13 · Q8 · 10 marks · 11-series streak
Marks in each of the last 12 Paper 1 sittingsOct/Nov 24May/Jun 26
Oct/Nov 24 · 13: 39 marksFeb/Mar 25 · 12: 28 marksMay/Jun 25 · 11: 26 marksMay/Jun 25 · 12: 22 marksMay/Jun 25 · 13: 12 marksOct/Nov 25 · 11: 34 marksOct/Nov 25 · 12: 20 marksOct/Nov 25 · 13: 7 marksFeb/Mar 26 · 12: 10 marksMay/Jun 26 · 11: 22 marksMay/Jun 26 · 12: 38 marksMay/Jun 26 · 13: 22 marks

What the papers say

  • Set in 25 of 25 Paper 1 sittings on the current syllabus — treat it as certain.
  • Worth about 21.1 marks a paper (28% of Paper 1, 1.7× its fair share).
  • Last set May/Jun 2026 · 0478/13 · Q8 for 10 marks — in the most recent series.
  • Set in each of the last 11 series without a miss.
  • Steady at around 22.2 marks a paper year on year.
  • Lives on “Give” and “Explain” — 69% of its questions: short, precise answers in syllabus words.
  • Most of its marks (88%) come in extended questions of 6+ marks — plan the answer before writing.
  • Its biggest question so far: 24 marks (Oct/Nov 2024 · 2210/13 · Q2).
  • Inside the topic, §1.1 Number systems carries the most marks (51%) and §1.1 Binary arithmetic the least (7%).
  • It is examined as a mix: AO1 48%, AO2 39% — definitions and descriptions in syllabus words score.
  • The examiner has commented on 123 of its questions — read “What the examiner said” before you practise.

Command words

Share of questions using the word (a question can use several). What each wants →

Question shapes

  • 1–2 mk4
  • 3–4 mk26
  • 5–6 mk40
  • 7–9 mk45
  • 10+ mk59

Average 8.9 marks a question · 16% with a figure or table · 34% with code · biggest 24 marks

Assessment objectives — how it is examined

Every part of every current-syllabus question filed under Cambridge's AO1 / AO2 / AO3 (from its command word and what it asks you to do), so you know whether this topic pays for definitions, for applying, or for judging and building.

  • AO1 Knowledge & understanding
  • AO2 Apply to a context
  • AO3 Evaluate & judge

Paper 1 as a whole

Paper 1SyllabusMeasured
AO1 Knowledge & understanding60%64%
AO2 Apply to a context20%24%
AO3 Evaluate & judge20%12%

Syllabus = Cambridge's grid; measured = the bank's current-syllabus papers.

Inside the topic — every syllabus bullet, measured

Each part of each question is filed under the bullet it examines; the numbers are per Paper 1 sitting, exactly like the topic's. Open a bullet for its own Statometer.

  • 1.1Number systems#1 of 20 on Paper 1Banker · 9490% next paper6.9 marks24/25 sittings May/Jun 2026

    Asked in nearly every paper — the bullet to know cold.Syllabus: why computers use binary; denary, binary and hexadecimal; converting between them (up to 16 bits); where hexadecimal is used and why

    Next Paper 1
    90%
    9 in 10
    Marks a paper
    6.9
    9% of the paper · 51% of the topic
    Asked in
    24 / 25
    Paper 1 sittings · 94 questions
    Last asked
    May/Jun 2026
    0478/13 · Q8 · 10 marks · 11-series streak
    • Asked in 24 of 25 Paper 1 sittings — nearly every paper.
    • About 6.9 marks a paper (9% of Paper 1; 51% of the topic's marks across its 4 bullets).
    • Last asked May/Jun 2026 · 0478/13 · Q8 (10 marks) — in the most recent series.
    • Asked in each of the last 11 series.
    • Usually “Give” or “Convert”: short, precise answers in syllabus words.
    • Biggest chunk of marks so far: 11 in May/Jun 2024 · 0478/13 · Q3.
    • It is examined mostly as AO2 (Apply to a context, 61%), the rest AO1 (33%) — you must apply it to the scenario or the given data — a definition alone will not score.
    Last 12 sittings Steady
    Oct/Nov 24 · 13: 6 marksFeb/Mar 25 · 12: 8.5 marksMay/Jun 25 · 11: 12 marksMay/Jun 25 · 12: 6.5 marksMay/Jun 25 · 13: 6 marksOct/Nov 25 · 11: 9 marksOct/Nov 25 · 12: 10 marksOct/Nov 25 · 13: 0 marksFeb/Mar 26 · 12: 3 marksMay/Jun 26 · 11: 5.5 marksMay/Jun 26 · 12: 7.5 marksMay/Jun 26 · 13: 10 marks

    Assessment objectives

    • AO1 Knowledge & understanding
    • AO2 Apply to a context
    • AO3 Evaluate & judge
    • Give59%
    • Convert42%
    • Show33%
    • Explain32%
  • 1.1Binary arithmetic#11 of 20 on Paper 1Regular · 5476% next paper2.6 marks20/25 sittings May/Jun 2026

    Set most sessions for a few marks; know the definition and one example.Syllabus: adding two 8-bit integers; overflow; logical left and right shifts; two's complement for positive and negative 8-bit integers

    Next Paper 1
    76%
    8 in 10
    Marks a paper
    2.6
    4% of the paper · 7% of the topic
    Asked in
    20 / 25
    Paper 1 sittings · 25 questions
    Last asked
    May/Jun 2026
    2210/12 · Q1 · 2.5 marks · 10-series streak
    • Asked in 20 of 25 Paper 1 sittings — about 8 papers in 10.
    • About 2.6 marks a paper (4% of Paper 1; 7% of the topic's marks across its 4 bullets).
    • Last asked May/Jun 2026 · 2210/12 · Q1 (2.5 marks) — in the most recent series.
    • Asked in each of the last 10 series.
    • Usually “Give” or “Show”: short, precise answers in syllabus words.
    • Biggest chunk of marks so far: 6 in Oct/Nov 2023 · 2210/12 · Q2.
    • It is examined almost entirely as AO2 (Apply to a context, 77%) — you must apply it to the scenario or the given data — a definition alone will not score.
    Last 12 sittings Steady
    Oct/Nov 24 · 13: 5 marksFeb/Mar 25 · 12: 2.5 marksMay/Jun 25 · 11: 0 marksMay/Jun 25 · 12: 4.5 marksMay/Jun 25 · 13: 1 marksOct/Nov 25 · 11: 3 marksOct/Nov 25 · 12: 4 marksOct/Nov 25 · 13: 0 marksFeb/Mar 26 · 12: 4 marksMay/Jun 26 · 11: 4.5 marksMay/Jun 26 · 12: 2.5 marksMay/Jun 26 · 13: 0 marks

    Assessment objectives

    • AO1 Knowledge & understanding
    • AO2 Apply to a context
    • AO3 Evaluate & judge
    • Give88%
    • Show72%
    • Convert52%
    • State36%
  • 1.2Text, sound and images#10 of 20 on Paper 1Core · 5873% next paper3.1 marks19/25 sittings May/Jun 2026

    A regular earner inside the topic — most papers touch it.Syllabus: character sets (ASCII, Unicode); sample rate and sample resolution; pixels, image resolution and colour depth; effects on file size and quality

    Next Paper 1
    73%
    7 in 10
    Marks a paper
    3.1
    4% of the paper · 14% of the topic
    Asked in
    19 / 25
    Paper 1 sittings · 40 questions
    Last asked
    May/Jun 2026
    0478/13 · Q1 · 3 marks
    • Asked in 19 of 25 Paper 1 sittings — about 8 papers in 10.
    • About 3.1 marks a paper (4% of Paper 1; 14% of the topic's marks across its 4 bullets).
    • Last asked May/Jun 2026 · 0478/13 · Q1 (3 marks) — in the most recent series.
    • Usually “Give” or “Explain”: short, precise answers in syllabus words.
    • Biggest chunk of marks so far: 11 in Oct/Nov 2023 · 0478/11 · Q5.
    • It is examined mostly as AO1 (Knowledge & understanding, 60%), the rest AO2 (30%) — definitions and descriptions in syllabus words score.
    Last 12 sittings Steady
    Oct/Nov 24 · 13: 4 marksFeb/Mar 25 · 12: 1 marksMay/Jun 25 · 11: 4 marksMay/Jun 25 · 12: 3 marksMay/Jun 25 · 13: 3 marksOct/Nov 25 · 11: 3 marksOct/Nov 25 · 12: 0 marksOct/Nov 25 · 13: 5 marksFeb/Mar 26 · 12: 0 marksMay/Jun 26 · 11: 8 marksMay/Jun 26 · 12: 3 marksMay/Jun 26 · 13: 3 marks

    Assessment objectives

    • AO1 Knowledge & understanding
    • AO2 Apply to a context
    • AO3 Evaluate & judge
    • Give55%
    • Explain45%
    • State35%
    • Identify28%
  • 1.3Data storage and compression#7 of 20 on Paper 1Core · 6881% next paper4 marks21/25 sittings May/Jun 2026

    A regular earner inside the topic — most papers touch it.Syllabus: bit, nibble, byte, KiB … EiB (1024-based); calculating image and sound file sizes; why compress; lossy vs lossless (run-length encoding)

    Next Paper 1
    81%
    8 in 10
    Marks a paper
    4
    5% of the paper · 28% of the topic
    Asked in
    21 / 25
    Paper 1 sittings · 78 questions
    Last asked
    May/Jun 2026
    0478/13 · Q1 · 4 marks · 7-series streak
    • Asked in 21 of 25 Paper 1 sittings — about 8 papers in 10.
    • About 4 marks a paper (5% of Paper 1; 28% of the topic's marks across its 4 bullets).
    • Last asked May/Jun 2026 · 0478/13 · Q1 (4 marks) — in the most recent series.
    • Asked in each of the last 7 series.
    • Rising: 3.4 → 4.5 marks a paper.
    • Usually “Give” or “Explain”: short, precise answers in syllabus words.
    • Biggest chunk of marks so far: 8 in Feb/Mar 2025 · 0478/12 · Q2.
    • It is examined mostly as AO1 (Knowledge & understanding, 59%), the rest AO3 (31%) — definitions and descriptions in syllabus words score.
    Last 12 sittings Rising
    Oct/Nov 24 · 13: 7 marksFeb/Mar 25 · 12: 8 marksMay/Jun 25 · 11: 8 marksMay/Jun 25 · 12: 5 marksMay/Jun 25 · 13: 0 marksOct/Nov 25 · 11: 4 marksOct/Nov 25 · 12: 0 marksOct/Nov 25 · 13: 2 marksFeb/Mar 26 · 12: 3 marksMay/Jun 26 · 11: 4 marksMay/Jun 26 · 12: 9 marksMay/Jun 26 · 13: 4 marks

    Assessment objectives

    • AO1 Knowledge & understanding
    • AO2 Apply to a context
    • AO3 Evaluate & judge
    • Give54%
    • Explain41%
    • State40%
    • Identify30%

33% of the topic's marks sit in question parts that belong to another topic (scenario questions cross sections) or that no bullet claims; they count for the topic, not for a bullet.

Marks a paper, year by year

11121314151617181920212223242526

Grey years are the previous syllabus (20112022, 120 questions) — history, not counted in the rates.

By exam series

  • Feb/Mar4/4 · 17.8 mk
  • May/Jun12/12 · 19.8 mk
  • Oct/Nov9/9 · 23 mk

What you need to know4syllabus §1.1, §1.2, §1.3

  1. 1.1Number systemswhy computers use binary; denary, binary and hexadecimal; converting between them (up to 16 bits); where hexadecimal is used and why
  2. 1.1Binary arithmeticadding two 8-bit integers; overflow; logical left and right shifts; two's complement for positive and negative 8-bit integers
  3. 1.2Text, sound and imagescharacter sets (ASCII, Unicode); sample rate and sample resolution; pixels, image resolution and colour depth; effects on file size and quality
  4. 1.3Data storage and compressionbit, nibble, byte, KiB … EiB (1024-based); calculating image and sound file sizes; why compress; lossy vs lossless (run-length encoding)

Video lectures44ZAK's YouTube channel · play here

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Infographics5draw these the way the examiner expects · download as PNG

Number system conversionsDenary ↔ binary ↔ hexadecimal — the routes the exam expects.Denarybase 10 · 0–9Binarybase 2 · 0,1Hexbase 16 · 0–9, A–F÷2, read remainders upadd place values 128…1group 4 bits → digiteach digit → 4 bitsdenary ↔ hex: go via binary (or ÷16 / ×16)128643216842110110110= 128+32+16+4+2= 182 = B6₁₆Two's complement: invert all bits, add 1. Left shift ×2, right shift ÷2.Hex is used for MAC addresses, colour codes, memory dumps and error codes.cswithzak.com

Number system conversions

O LevelAS
File size calculationsWork in bits first, then ÷ 8 for bytes, then ÷ 1024 for each step up. Show every line of working.IMAGE (bitmap)size = width × height × colour depth1024 × 768 × 24 bits= 18 874 368 bits ÷ 8= 2 359 296 bytes ÷ 1024= 2304 KiB = 2.25 MiBcolour depth 24 bits = 16.7 million colours (2²⁴)SOUNDsize = sample rate × resolution × seconds44 100 Hz × 16 bits × 30 s= 21 168 000 bits ÷ 8= 2 646 000 bytes ÷ 1024≈ 2584 KiB ≈ 2.52 MiB (×2 if stereo)higher sample rate / resolution = better quality, bigger filebitnibble×4byte×2KiB×1024MiB×1024GiB×1024TiB×1024PiB×1024EiB×10241 nibble = 4 bits · 1 byte = 8 bits · 1 KiB (kibibyte) = 1024 bytes · 1 MiB = 1024 KiB · 1 GiB = 1024 MiB · 1 TiB = 1024 GiBBinary prefixes (kibi, mebi, gibi…) are powers of 2. Decimal prefixes (kilo, mega, giga…) are powers of 10: 1 kB = 1000 bytes.Resolution = number of pixels (w × h). Colour depth = bits per pixel.Sample rate = samples per second (Hz). Sample resolution = bits per sample.Compression: lossy (MP3, JPEG) discards data permanently; lossless (RLE, PNG, ZIP) restores the original exactly.cswithzak.com

File size calculations

O LevelAS
Two's complement, overflow & shifts8-bit two's complement: the MSB is worth −128. Range −128 … +127. Same bits, different meaning — saywhich you are using.Negating +37 → −37+370010010132 + 4 + 1invert11011010flip every bit (one’s complement)+111011011= −128 + 64 + 16 + 8 + 2 + 1 = −37 ✓Shortcut: from the right, copy up to and including the first 1, then flip the rest.Overflow0111111112700000001+ 110000000= −128 ✗ does not fit in 8 bitsOverflow = the answer needs more bits than the register has.Sign flips: two positives give a negative (or vice-versa).ShiftsShift0001 0110 (22) →logical left 10010 1100 (44)logical right 10000 1011 (11)arithmetic right 1keeps the sign bit1111 0100 (−12) →1111 1010 (−6)Left ×2, right ÷2. Bits shifted out are lost — that isanother cause of overflow. Logical fills with 0s.BCD: each denary digit as its own 4-bit nibble — 47 = 0100 0111. Used where exact decimals matter (currency).cswithzak.com

Two's complement, overflow & shifts

O LevelAS
Bitmap vs vector graphics & digital soundBitmap = grid of pixels. Vector = list of drawing commands. Sound = analogue wave measured (sampled) atregular intervals.BITMAP8 × 6 pixels · 1 bit eachVECTORellipse(56,42,44,30) line(…)BitmapVectorStored ascolour of every pixelobjects + propertiesResizepixelates / blursscales perfectlyFile sizeresolution × colour depthdepends on object countBest forphotos, scanslogos, fonts, CAD, mapsFormatsBMP, JPEG, PNG, GIFSVG, EPS, AIImage resolution = pixels per inch / total pixels. Colour depth = bits per pixel: 1 bit → 2 colours, 8 bits → 256, 24 bits → 16.7 M.File header stores width, height, colour depth. 2210/9618 both want: file size = W × H × depth (+ header).Sampling sound111100000Sampling rate = samples per second (Hz). CD quality = 44.1 kHz.Sampling resolution = bits per sample (8 levels shown = 3 bits).Higher rate → closer to the analogue wave; higher resolution →finer amplitude steps. Both increase the file size.size = rate × resolution × seconds (× 2 for stereo).Vector = drawing list, bitmap = colour of every pixel — so a vector logo scales cleanly and a bitmap photo does not.cswithzak.com

Bitmap, vector & sound

ASO Level
Lossless vs lossy compressionWhy compress? Less storage, faster transmission, less bandwidth. The question is whether you can get theoriginal back.LOSSLESSoriginal restored exactly — RLE, ZIP, PNG, FLAC, GIFLOSSYdetail discarded for ever — JPEG, MP3, MP4, AACRun-length encoding (RLE)AAAABBBCCDAA4A3B2C1D2A12 → 10 bytes. RLE wins only with long runs (flat colour areas).Also: LZ (repeated patterns), Huffman (short codes, common symbols).What lossy actually removesImages (JPEG): merge near-identical colours, reduce colour depthor resolution — the eye cannot tell the difference.Sound (MP3): remove frequencies humans cannot hear, quietersounds masked by louder ones; lower sample rate / resolution.Video (MPEG): store only the changes between frames.Result: much smaller files, but quality is permanently lower.LosslessLossyData lost?none — bit-for-bit identical after decompressionyes — cannot recover the originalCompression ratiolower (depends on the data)much higher (adjustable quality)Use whentext, programs, spreadsheets, medical imagesphotos, music, streaming videoExam tip: if the question says “the file must be restored exactly” → lossless; “smallest possible for the web” → lossy.cswithzak.com

Lossless vs lossy compression

ASO Level

Browse all infographics →

Key terms10use these exact words in the exam

binaryhexadecimaltwo's complementoverflowASCIIUnicodesample rateresolutioncolour depthcompression

Dotted terms are defined in the glossary.

Code help3referenced to the Cambridge pseudocode guide

Denary → binary by repeated division

pseudocode 2210 §8 loops / DIV & MOD Run in Playground
DECLARE N, Bit : INTEGER
DECLARE Binary : STRING
N 182
Binary ""
REPEAT
Bit N MOD 2
Binary NUM_TO_STR(Bit) & Binary // remainders read bottom-up
N N DIV 2
UNTIL N = 0
OUTPUT Binary

💡 Exactly the method the mark scheme wants: divide by 2, collect remainders in reverse.

Binary → denary with place values

pseudocode Run in Playground
DECLARE B : STRING
DECLARE i, Total, Place : INTEGER
B "10110110"
Total 0
Place 1
FOR i LENGTH(B) TO 1 STEP -1
IF SUBSTRING(B, i, 1) = "1" THEN
Total Total + Place
ENDIF
Place Place * 2
NEXT i
OUTPUT Total

Logical shift = multiply/divide by 2

pseudocode Run in Playground
DECLARE V : INTEGER
V 22 // 0001 0110
OUTPUT V * 4 // shift left 2 → 88
OUTPUT V DIV 2 // shift right 1 → 11

Playground examples7runnable programs for this topic

  • Denary → binary by repeated division

    MOD 2 gives each bit, DIV 2 moves on; the remainders are read bottom-up.

    O LevelASPseudocodeTheory in code 2210 §1.1 / 9618 §1.1
    Run
  • Binary → denary with place values

    Walk the bits from the right, doubling the place value each time.

    O LevelASPseudocodeTheory in code 2210 §1.1 / 9618 §1.1
    Run
  • Denary → hexadecimal

    Same idea as binary but MOD 16, with a lookup string for the digits A–F.

    O LevelASPseudocodeTheory in code 2210 §1.1 / 9618 §1.1
    Run
  • Two's complement — negate an 8-bit number

    Invert every bit, then add 1 with a carry that ripples from the right.

    O LevelASPseudocodeTheory in code 2210 §1.1 / 9618 §1.1
    Run
  • Run-length encoding (lossless compression)

    Replace runs of the same character with a count and the character.

    O LevelASPseudocodeTheory in code 2210 §1.3 / 9618 §1.3
    Run
  • Binary, hex and two's complement

    bin(), hex(), int(s, 2) and format() — plus two's complement of a negative number by hand.

    O LevelASPythonTheory in code 2210 §1 / 9618 §1
    Run
  • Logic gates and a truth table

    Build AND, OR, XOR, NAND from Boolean operators and print the truth table of an expression.

    O LevelASPythonTheory in code 2210 §10 / 9618 §3
    Run

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