Unit 4: Data Structures

4.1 Array

• Represent collections of related primitive or object reference data using one-dimensional (1D) array objects.

• Traverse the elements in a 1D array.

• Traverse the elements in a 1D array object using an enhanced for loop.

• For algorithms in the context of a particular specification that requires the use of array traversals:

  • Identify standard algorithms.

  • Modify standard algorithms.

  • Develop an algorithm.

4.2 ArrayList

• Represent collections of related object reference data using ArrayList objects.

• For ArrayList objects:

  • Traverse using a for or while loop

  • Traverse using an enhanced for loop

• For algorithms in the context of a particular specification that requires the use of ArrayList traversals:

  • Identify standard algorithms.

  • Modify standard algorithms.

  • Develop an algorithm.

4.3 2D Array

• Develop code used to represent collections of related data using two-dimensional (2D) array objects.

• Develop code used to traverse the elements in a 2D array and determine the result of these traversals.

• Develop code for standard and original algorithms for a particular context or specification that involves 2D arrays and determine the result of these algorithms.

4.4 Search and Sort Algorithms

• Apply sequential/linear search algorithms to search for specific information in array or ArrayList objects.

• Apply selection sort and insertion sort algorithms to sort the elements of array or ArrayList objects.

• Compute statement execution counts and informal run-time comparison of sorting algorithms.

• Apply recursive search algorithms to information in String, 1D array, or ArrayList objects.

• Apply recursive algorithms to sort elements of array or ArrayList objects.

• Explain the risks to privacy from collecting and storing personal data on computer systems.

4.5 Ethical and Social Issues Around Data Collection

• Explain the risks to privacy from collecting and storing personal data on computer systems.

• Explain the importance of recognizing data quality and potential issues when using a data set.

• Identify an appropriate data set to use in order to solve a problem or answer a specific question.