Run-Length Encoding · Dictionary Coding · No Data Lost
CSZoneAQA GCSE Computer Science 8525
Why Compress?
Reducing File Size
Compression reduces file size so files take less storage space and can be transmitted faster over a network. Lossless compression reduces size without losing any data — the original file can be perfectly reconstructed.
Used for: text files, source code, databases, PNG images, ZIP archives
The decompressed file is identical to the original — no data is ever lost
Essential when exact data matters — e.g. medical records, financial data, executable programs
Run-Length Encoding (RLE)
Counting Repeating Values
RLE replaces consecutive repeated values with a count and value pair. Highly effective for data with long runs of the same value (e.g. simple images).
Dictionary coding (used in ZIP, LZ77, LZW) builds a dictionary of repeated patterns during compression. Repeated phrases are replaced with short codes. Common in text and source code.
Original text: "the cat sat on the mat near the hat"
Dictionary entry: [01] = "the "
Compressed: "[01]cat sat on [01]mat near [01]hat"
Each occurrence of "the " is replaced with a 2-byte code.
Exam Practice
Have a go at this question
AQA-style question
The following image row is to be compressed using Run-Length Encoding: ■■■■□□■■■■■□□□□ (a) Write the RLE representation. (b) How many values has RLE reduced it from and to?
3 marks
(a) 4■ 2□ 5■ 4□ [2] (b) 15 values → 8 values [1]
Key Takeaways
What to Remember
Lossless compression — reduces size, original can be perfectly reconstructed
RLE — replaces runs of repeated values with count + value
Dictionary coding — replaces repeated phrases with short codes
Used for: text, programs, medical/financial data — any file where exact reproduction is required