Lesson 4.4.1.11

4.4.1.11 Automation Quiz: AQA Computer Science, Unit 4

20 questions

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Lesson 4.4.1.11, Automation: 20 multiple choice questions for the AQA Computer Science (7517), Unit 4: Theory of computation, written with Revision Ninja.

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The 20 questions

  1. What does automation require, according to the specification?

    • Writing programs without algorithms
    • Putting models of real-world objects into action to solve problems
    • Storing data without any structure
    • Replacing all human involvement with hardware that runs without any software
  2. Which step is part of the process of automation?

    • Creating algorithms to act on the modelled data
    • Deleting the model after it is built
    • Avoiding any execution of code
    • Printing the source code only and filing a copy of it in a paper archive
  3. Which of these is NOT one of the four routes to automation listed in the specification?

    • Creating algorithms that act on the modelled data and their structures
    • Implementing models in data structures
    • Waiting for the model to implement itself
    • Implementing algorithms in program code
  4. Why do computer scientists choose what to include in a model?

    • To keep only the minimum detail needed to solve the problem to the required accuracy
    • To include every possible detail of the real world, so that the model is exact and complete
    • To avoid any choice at all
    • To make the model as large as possible
  5. What does the specification describe computer science as dealing with in relation to models?

    • Putting models into action to solve problems
    • Only storing photographs of the real world
    • Avoiding abstraction altogether
    • Only measuring hardware temperatures
  6. In automation, what does 'implementing the models in data structures' mean?

    • Representing modelled objects and their links with suitable data structures
    • Converting the model into a sound file
    • Writing a document about the model
    • Drawing a detailed diagram of the model on paper with labels for every single part
  7. Which list correctly orders the parts of automation?

    • Create algorithms, implement them in code, model the data, execute the code
    • Print the model, then delete it
    • Execute the code first, then create algorithms, and implement data structures last
    • Implement data structures only
  8. A traffic simulation models cars as objects with speed and position. Which step of automation is this?

    • Executing code only
    • Hand-tracing a sorting algorithm
    • Implementing the models in data structures
    • Writing a legal contract
  9. Which statement about efficiency in automation is most accurate?

    • Efficiency only concerns the screen size
    • Efficiency means making the model as detailed as possible, with every last attribute recorded
    • Efficiency is irrelevant once code is written
    • Efficient automation uses models and algorithms that run quickly with little memory
  10. A model removes irrelevant detail so that an algorithm can run quickly. Which principle is this?

    • Hardware failure
    • Abstraction in service of automation
    • Data corruption
    • Random guessing at which details to keep, adjusted by trial and error
  11. Which is the best description of 'executing the code' in automation?

    • Saving the program to a backup folder
    • Running the program so that the model acts on data to solve the problem
    • Printing the program in a book
    • Saving the program to a backup folder and then deleting the original copy so only the backup remains
  12. A school timetabling model stores rooms and lessons as records and runs an algorithm to assign them. Which parts of automation are present?

    • Modelling in data structures, an algorithm and execution of code
    • Only a printed poster
    • Only a list of names with no data structure
    • Only a hand-drawn sketch with no algorithm
  13. Why does the specification stress that automation depends on abstraction?

    • Because abstraction is only needed in classroom exercises and never in real computing systems
    • Because abstraction makes code run slower
    • Because models must copy the real world exactly
    • Because real-world objects are messy and must be modelled by choosing what matters
  14. What is the relationship between a model and an algorithm in automation?

    • The model is a type of algorithm
    • The algorithm performs actions on the data the model describes
    • They never interact
    • The algorithm replaces the model entirely
  15. Which example best demonstrates automation?

    • A teacher writing marks by hand each time, then adding them up on a calculator
    • A program that calculates and prints exam results from a stored list of marks
    • A paper form with no computation
    • A stone tablet with carvings
  16. Which statement about automation is correct?

    • It cannot involve data structures
    • It needs no model at all
    • It requires an algorithm, a model, and code that is executed
    • It is only possible with a graphical display
  17. A bank automates interest calculations. Which element of automation is the model?

    • The printer used for statements
    • The interest algorithm only
    • The account records with balances and interest rates as stored data
    • The keyboard used by staff
  18. Which activity belongs to automating a task with a computer?

    • Writing a letter by hand
    • Creating an algorithm to act on the modelled data
    • Drawing a picture of the room
    • Counting paper sheets manually with a pencil and recording each total on a form
  19. In automation, what is a model?

    • A complete copy of every detail of the real world, including each atom and every event
    • An abstraction of a real-world object or phenomenon, keeping only the detail needed
    • A photograph of an object
    • A random list of values
  20. Which step comes before the others when automating a problem?

    • Modelling the real-world problem as objects and data
    • Deleting the old data permanently
    • Buying new hardware for the office
    • Running the finished program on real users before any model or algorithm has been designed

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