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AP® Computer Science Principles · Unit 3 · Topic 3.2

Data Abstraction: Topic Checklist (Computer Science Principles 3.2)

Specific "I can" statements for data abstraction and lists, each linked to the study-guide section or practice question that tests it.

Work through the list without notes. If you cannot do a statement, follow the pointer, then come back. Guide = the study guide; Practice = the practice questions.

Understanding

  • I can define a data abstraction using the idea of separating abstract properties from concrete representation (Guide: What data abstraction is)
  • I can describe a list as an ordered sequence of elements with indices (Guide: Lists: the abstraction you must know; Practice: Question 1)
  • I can state that in the exam notation the first index is 1 (Guide: Lists; Practice: Questions 1 and 2)
  • I can give three ways data abstraction manages complexity (Guide: What data abstraction is; Practice: Question 6)

Skills

  • I can create a list and an empty list in the reference notation (Guide: Lists; Practice: Question 3)
  • I can read and assign list elements by index (Guide: Lists; Practice: Question 9)
  • I can use LENGTH to refer to the last element (Guide: Lists; Practice: Question 2)
  • I can work with a list that holds different types of element (Guide: Lists (mixed types); Practice: Question 5)
  • I can predict when an index is invalid and what happens (Guide: Lists (index errors); Practice: Question 4)

Reasoning

  • I can compare a program with and without a list and say which adapts better (Guide: Worked example 1; Practice: Question 7)
  • I can write the four-part explanation of how an abstraction manages complexity (Guide: Worked example 2; Practice: Question 8)
  • I can decide whether an abstraction hides too much or too little detail for a program’s purpose (Guide: Choosing what the abstraction hides)

When every line is secure, move on. The revision notes are here: revision notes.

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