APS Test 1
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Questions and Answers

What is the primary purpose of an algorithm?

  • To test a program
  • To design a solution
  • To represent a problem
  • To provide a set of specific step-by-step instructions (correct)

    • An algorithm should have a defined starting point and ending point.

    True

    What is the importance of unit-testing during the assembly of an algorithm?

    Reveals incomplete or missing logic

    Algorithms can be represented in two ways: __________________ and Flowchart.

    <p>Pseudo code</p> Signup and view all the answers

    What is the best use of Pseudo code?

    <p>To provide the framework of the program without specific syntax</p> Signup and view all the answers

    Flowcharts are only used to visualize a very specific small section of logic.

    <p>True</p> Signup and view all the answers

    What should be done when incomplete or missing logic is identified during unit-testing?

    <p>Revisit the other stages to review and reassess</p> Signup and view all the answers

    The last step in the algorithm design process is to perform an __________________ test of the entire solution.

    <p>OVERALL</p> Signup and view all the answers

    Match the following representations of algorithms with their best uses:

    <p>Pseudo code = Best used for computer programmers Flowchart = Best used to communicate process to non-technical business persons</p> Signup and view all the answers

    Algorithms can refer to other algorithms when necessary.

    <p>True</p> Signup and view all the answers

    What is the main approach to problem solving that programmers use?

    <p>Computational Thinking</p> Signup and view all the answers

    Programmers can create a solution to a problem without fully understanding the problem.

    <p>False</p> Signup and view all the answers

    What is the process of breaking down complex problems into more manageable parts?

    <p>Decomposition</p> Signup and view all the answers

    Before creating a solution, programmers must ____________________ the problem.

    <p>fully understand</p> Signup and view all the answers

    Match the following to their respective definitions:

    <p>Decomposition = Pattern recognition &amp; data representation Breaking down complex problems = Identifying patterns in data</p> Signup and view all the answers

    What is the next step after decomposition in the computational thinking approach?

    <p>Pattern recognition &amp; data representation</p> Signup and view all the answers

    Computational thinking is only used in software development.

    <p>False</p> Signup and view all the answers

    What is the main benefit of decomposition in problem-solving?

    <p>Breaking down complex problems into manageable parts</p> Signup and view all the answers

    Computational thinking involves ____________________ parts: decomposition, pattern recognition & data representation, abstraction, and algorithms.

    <p>four</p> Signup and view all the answers

    Why is it important to understand the problem before creating a solution?

    <p>To ensure the solution is correct</p> Signup and view all the answers

    What is the main goal of pattern recognition and data representation in computational thinking?

    <p>To identify common behavior and attributes</p> Signup and view all the answers

    Abstraction is about including specific details to form an idea or concept.

    <p>False</p> Signup and view all the answers

    What is the benefit of abstraction in problem-solving?

    <p>Abstraction declutters characteristics of a problem and solution of unnecessary details, ensuring the solution addresses the problem.</p> Signup and view all the answers

    The process of breaking down a complex problem into smaller, manageable parts is called ______________.

    <p>decomposition</p> Signup and view all the answers

    What is the primary focus of the abstraction stage in computational thinking?

    <p>Generalizing characteristics of a problem</p> Signup and view all the answers

    Pattern recognition is a stage that comes after decomposition in computational thinking.

    <p>True</p> Signup and view all the answers

    What is the importance of filtering out specific details in abstraction?

    <p>It ensures the solution addresses the problem and prevents producing a solution that doesn't address the problem.</p> Signup and view all the answers

    The cakes example illustrates how abstraction can help to ______________ unnecessary details.

    <p>declutter</p> Signup and view all the answers

    Match the following stages of computational thinking with their descriptions:

    <p>Decomposition = Breaking down a complex problem into smaller parts Pattern recognition &amp; data representation = Identifying common behavior and attributes Abstraction = Filtering out specific details to form an idea or concept Algorithms = Designing a step-by-step solution</p> Signup and view all the answers

    Data representation is a part of the decomposition stage in computational thinking.

    <p>False</p> Signup and view all the answers

    What is the main purpose of the decomposition stage in computational thinking?

    <p>To determine the scope of your solution</p> Signup and view all the answers

    Pattern recognition is only important in the decomposition stage.

    <p>False</p> Signup and view all the answers

    What is one benefit of identifying patterns in data?

    <p>Simplifies the solution and makes it more efficient</p> Signup and view all the answers

    The decomposition stage helps answer the question _______________.

    <p>Where do I begin?</p> Signup and view all the answers

    What is an example of a data structure that could be defined for an 'ingredient'?

    <p>Description/name and amount/quantity</p> Signup and view all the answers

    The decomposition stage is the final stage of computational thinking.

    <p>False</p> Signup and view all the answers

    What is one thing that the decomposition stage helps determine?

    <p>What you need to focus on to build a solution</p> Signup and view all the answers

    Match the following stages of computational thinking with their descriptions:

    <p>Decomposition = Determine the scope of your solution Pattern Recognition = Identify commonality in process and data Abstraction = Not mentioned in the content Algorithms = Not mentioned in the content</p> Signup and view all the answers

    Identifying patterns in data can make the solution more _______________.

    <p>efficient</p> Signup and view all the answers

    The decomposition stage is only about identifying patterns in data.

    <p>False</p> Signup and view all the answers

    Abstraction involves recognizing that two things differ only in small ways and moving the small differences into parameters. What does this allow?

    <p>Retaining the fundamental problem-solving technique</p> Signup and view all the answers

    Abstraction is about including specific details to form an idea or concept.

    <p>False</p> Signup and view all the answers

    What is the purpose of abstraction in problem-solving?

    <p>To filter out unnecessary details and focus on the essential characteristics of a problem</p> Signup and view all the answers

    In computational thinking, abstraction involves moving the small differences into _______________

    <p>parameters</p> Signup and view all the answers

    Match the stages of computational thinking with their descriptions:

    <p>Decomposition = Breaking down complex problems into manageable parts Abstraction = Filtering out unnecessary details to focus on essential characteristics Pattern Recognition = Identifying patterns in data to inform solutions</p> Signup and view all the answers

    What is the process of breaking down a complex problem into smaller, manageable parts?

    <p>Decomposition</p> Signup and view all the answers

    Swapping values in an array is a simple process.

    <p>False</p> Signup and view all the answers

    What is the purpose of the decomposition stage in computational thinking?

    <p>To break down a complex problem into smaller, manageable parts.</p> Signup and view all the answers

    When solving a problem, we need to ____________________ the problem to understand its components.

    <p>decompose</p> Signup and view all the answers

    What is the next step after decomposition in the computational thinking approach?

    <p>Pattern recognition</p> Signup and view all the answers

    Computational thinking is only used in software development.

    <p>False</p> Signup and view all the answers

    What is the benefit of abstraction in problem-solving?

    <p>It helps to filter out unnecessary details and focus on the essential components of the problem.</p> Signup and view all the answers

    When swapping values in an array, we need to use a ____________________ variable to store the original value.

    <p>temp</p> Signup and view all the answers

    Match the following stages of computational thinking with their descriptions:

    <p>Decomposition = Breaking down a complex problem into smaller parts Abstraction = Identifying patterns and relationships between components Pattern recognition = Focusing on the essential components of the problem Algorithm design = Creating a step-by-step solution to the problem</p> Signup and view all the answers

    What is the main goal of pattern recognition in computational thinking?

    <p>To filter out unnecessary details and focus on the essential components</p> Signup and view all the answers

    What is the purpose of recognizing patterns in data?

    <p>To identify commonalities among different pieces of data</p> Signup and view all the answers

    Abstraction involves including specific details to form an idea or concept.

    <p>False</p> Signup and view all the answers

    What is the benefit of decomposition in problem-solving?

    <p>Breaking down complex problems into smaller, manageable parts</p> Signup and view all the answers

    The process of finding the maximum value in a series of values is an example of ____________________.

    <p>pattern recognition</p> Signup and view all the answers

    Match the following stages of computational thinking with their descriptions:

    <p>Decomposition = Breaking down complex problems into smaller, manageable parts Pattern Recognition = Identifying commonalities among different pieces of data Abstraction = Filtering out specific details to form an idea or concept</p> Signup and view all the answers

    What is the purpose of identifying patterns in data?

    <p>To identify commonalities among different pieces of data</p> Signup and view all the answers

    The decomposition stage is the final stage of computational thinking.

    <p>False</p> Signup and view all the answers

    What is the purpose of abstraction in problem-solving?

    <p>Filtering out specific details to form an idea or concept</p> Signup and view all the answers

    The process of breaking down complex problems into smaller, manageable parts is called ____________________.

    <p>decomposition</p> Signup and view all the answers

    What is the main focus of the abstraction stage in computational thinking?

    <p>Filtering out specific details to form an idea or concept</p> Signup and view all the answers

    Study Notes

    Understanding Problem Solving and Computational Thinking

    • Programmers think differently and must harness the computational thinking approach to problem solving, which paves the way for providing a solution that both computers and humans can understand.
    • Before solving a problem, it's essential to fully understand the problem, carefully read documentation, identify uncertainties, and clarify any unclear points.

    Computational Thinking Stages

    • There are 4 main parts to the computational thinking approach:
      • Decomposition
      • Pattern recognition and data representation
      • Abstraction
      • Algorithms

    Decomposition

    • Decomposition is the process of breaking down complex problems into more manageable parts.
    • It helps to identify and simplify complex problems, making them more manageable.
    • Example: Breaking down a morning routine into smaller tasks like waking up, showering, brushing teeth, getting dressed, eating breakfast, and going to work/school.

    Pattern Recognition and Data Representation

    • This stage involves identifying common behavior and attributes, making parts reusable and eliminating redundancies.
    • It simplifies solutions, makes them more efficient, and reduces repetition.
    • Example: Identifying patterns in baking different types of cakes, such as requiring specific ingredients, amounts, and temperatures.

    Abstraction

    • Abstraction concentrates on generalizing characteristics of a problem and/or pattern, filtering out specific details to form an idea or concept.
    • It declutters characteristics of a problem and solution, ensuring the solution addresses the problem.
    • Example: Abstraction in baking a cake, focusing on the general process rather than specific details like baking time and temperature.

    Algorithms

    • The final stage of computational thinking, representing a master plan with specific step-by-step instructions.
    • Algorithms can refer to other algorithms for larger problems and must include unit-testing during assembly.
    • Algorithms can be represented in two ways: pseudo code (best for programmers) and flowcharts (best for non-technical people).

    Abstraction

    • Abstraction involves recognizing that two things differ only in small ways and moving those small differences into parameters.
    • It involves retaining the fundamental problem-solving technique, focusing on the essential aspects of the problem.

    Abstraction Example

    • Finding the sum of 10 values and finding the product of 15 values are similar problems.
    • Both involve visiting a series of values and combining them into a single value.
    • The common aspect between these problems is the combination of values into a single value.
    • The differences between these problems are:
      • The operation to combine the values (e.g., +, -, *, /).
      • The number of values to combine.
      • The values themselves.

    Parameters in Abstraction

    • Make differences between similar problems into parameters.
    • Create a parameters table to organize and compare the differences between similar problems.
    • Example parameters table:
      • Operator (e.g., +, -, *, /)
      • Number of values to combine (# Values)
      • Values to combine

    Decomposition

    • Divide a problem into smaller, more manageable sub-problems.
    • Solve each sub-problem separately.
    • Combine solutions to sub-problems to yield a solution to the original problem.

    Example 1: Summing Several Values

    • Analyze the problem: need to sum multiple values.
    • Identify key requirements:
      • Need a place to store the sum.
      • Sum needs to be initialized to zero.
      • Need to access each of the values.
      • Need to add each value to the sum.
    • Solution:
      • Create and initialize sum.
      • Decompose the problem:
        • Access each value in turn by having the user enter values one at a time.
        • Add each value onto the sum.

    Example 2: Sorting Two Values in Ascending Order

    • Analyze the problem: need to sort two values in ascending order.
    • Identify key requirements:
      • Compare the first value to the second.
      • If out of order, swap them.
    • Solution:
      • Swapping values:
        • Use a third variable to store the first value when overwriting with the second.
        • Copy first value to temp.
        • Copy second value to first.
        • Copy temp to second value.
    • Putting it all together:
      • Compare first to second.
      • If out of order:
        • Copy first to temp.
        • Copy second to first.
        • Copy temp to second.

    Pattern Recognition in Data

    • Patterns in data involve looking for commonalities among several things, and factoring them out into a new piece of information that individual things can reference.
    • Examples of patterns in data include:
      • A cheque with common fields such as date, amount, and account number
      • A bank deposit with common fields such as date, amount, and account number

    Commonalities in Data

    • Commonalities in data include:
      • Date: a combination of day, month, and year
      • Amount: a simple number
      • Account: a bank identifier, branch ID, and account number

    Factorization of Complex Common Parts

    • Date can be broken down into:
      • Day
      • Month
      • Year
    • Account can be broken down into:
      • Bank
      • Branch
      • AcctNumber

    Patterns in Functionality

    • Patterns in functionality involve looking for the same operations performed in different places, and factoring out the repeating operations.
    • Example: finding the maximum of a series of values in both weather and expenses data.

    Commonality in Functionality

    • The commonality in functionality is finding the maximum value of a series of values.
    • This can be applied to:
      • Finding the hottest day from a list of temperatures
      • Finding the most expensive meal from a list of bills

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    Related Documents

    APS145-ComputationalThinking.pdf
    Computational-Thinking-Abstraction.pdf
    Computational-Thinking-Decomposition.pdf
    Computational Thinking - Pattern Recognition PDF

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