GCSE Computer Science OCR

This subject is broken down into 92 topics in 9 modules:

  1. Computer Systems 19 topics
  2. Computational Thinking, Algorithms and Programming 28 topics
  3. Components of a Computer System 8 topics
  4. Networks 7 topics
  5. Issues 3 topics
  6. Algorithms 5 topics
  7. Programming 10 topics
  8. Design, Testing and IDEs 4 topics
  9. Data Respresentations 8 topics
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  • 9
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  • 92
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  • 35,350
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  • 4+
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This page was last modified on 28 September 2024.

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Computer Science

Computer Systems

Computer Systems

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Computer Systems

Basics of Computer Systems

  • A computer system includes hardware, software, and data which all work together.
  • Hardware includes the physical components of a computer, like the CPU, memory, and input/output devices.
  • Software is the set of instructions that direct the hardware to carry out tasks.
  • Operating systems are a vital type of system software that controls overall operation of a computer.

Characteristics of Contemporary Processes, Software and Hardware

  • A process in computing is an instance of a program in execution. It needs resources like CPU time, memory, and files, and it can be made up of multiple threads.
  • Multithreading allows a computer to perform many different tasks at the same time.
  • Contemporary systems can also implement parallel processing, where many processors perform operations at the same time.
  • The speed of a processor is measured in gigahertz (GHz), while its power is measured in terms of the number of cores it has.

Systems Architecture

  • The CPU, or central processing unit, is considered the brain of the computer. It executes program instructions. The speed at which the CPU processes data is called clock speed.
  • Volatile memory, like RAM, requires power to keep the stored information accessible. Once the power is gone, the data is too.
  • Non-volatile memory, like a hard drive or flash memory, stores information even when not powered.
  • The motherboard is the main circuit board in a computer, housing the CPU, memory, and input/output device connections.

Software and Software Development

  • System software, like the operating system, coordinates and controls hardware functions.
  • Application software enables users to complete tasks, like word processing or web browsing.
  • A compiler translates the entire code of a program into machine code in one go, whereas an interpreter translates the code line by line, executing each line as it goes.
  • Low level programming languages, like assembler, are closer to machine code and specific to individual computer architectures.
  • High level programming languages, like Python or Java, are closer to human language and are easier to write, read, and maintain.

Exchanging Data

  • Networks are systems of interconnected computers that can send and share data.
  • LANS, or Local Area Networks, connect computers in a small geographical area, like a school.
  • WANS, or Wide Area Networks, cover a large geographical area, often made up of interconnected LANS.
  • Protocols are sets of rules that dictate how data should be transmitted across networks.
  • HTTP, or Hyper Text Transfer Protocol, is the protocol for transferring multimedia web pages.

Data Types, Data Structures and Algorithms

  • Computers use different data types like integer, character, or Boolean values.
  • A data structure is a specialized format for organizing and storing data, like arrays, stacks, and queues.
  • An algorithm is a set of instructions for solving a particular problem. It can be represented with pseudocode or a flowchart.

Legal, Moral, Cultural and Ethical Issues

  • Understanding the legal, moral, cultural, and ethical issues in computing is crucial. This includes topics like data protection, integrity, accessibility, and intellectual property.

Course material for Computer Science, module Computer Systems, topic Computer Systems

Computer Science

Computational Thinking, Algorithms and Programming

Data Representation: Compression

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Data Representation: Compression

Data Representation: Compression

Understanding Compression

  • Compression reduces the size of files to save storage space or to reduce the time taken to send files over a network.
  • It is broadly categorised into two types: lossless compression and lossy compression.

Lossless Compression

  • In lossless compression, the original data can be perfectly recovered when the file is uncompressed.
  • Examples include text file compression, ZIP file format, and PNG for images.
  • It is typically used in situations where absolute fidelity to the original data is necessary.

Lossy Compression

  • In lossy compression, some data from the original file is lost during compression.
  • The original data cannot be perfectly recovered in this case.
  • Examples include MP3 for audio and JPEG for images.
  • Despite some loss of data, users might not be able to discern any noticeable difference in quality. This is due to the compression algorithm eliminating data that is less important to human perception.
  • Lossy is generally used when a compromise between file size and exact fidelity to the original data is acceptable.

Understanding File Sizes

  • The size of a file is measured in bytes.
  • A kilobyte (KB) is approximately 1000 bytes, a megabyte (MB) is approximately 1000 kilobytes, a gigabyte (GB) is approximately 1000 megabytes, and so on.

Encoding and Compression

  • Encoding is the process of converting data from one form to another. It's used in both types of compression.
  • In compression, the most commonly used encoding technique is Huffman coding. It's a lossless compression method that assigns shorter codes to more frequently appearing characters in data.

Compression Ratio

  • The compression ratio measures how much a file is reduced in size by compression.
  • A higher compression ratio means a greater reduction in file size.

Importance of Compression

  • Compression is significant in minimising the storage space required for files and quickening the transfer speed of files over a network.
  • However, the choice between lossy and lossless depends on the specific requirements, whether it is more important to maintain quality or reduce size.

Course material for Computer Science, module Computational Thinking, Algorithms and Programming, topic Data Representation: Compression

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