Overview

This week, we’ll cover a lot of ground:

• complexity, continued, with examples and calculations,
  • auxiliary and space complexity;
• trees:
  • rooted trees,
  • binary trees,
  • some applications of trees;
  • tree traversal and search:
    • depth-first search and breadth-first search,
    • pre-order and post-order traversal,
    • in-order traversal of binary trees; and
  • expression trees.

If there’s a discrepancy between any dates, grade weights, or policies between what’s stated in videos and the syllabus, the syllabus prevails.

Learning Objectives

By the end of this module, you will be able to:

• describe how trees are used to represent data,
• explain how we find values in a binary search tree, and
• understand how small changes in a search algorithm can yield different traversals (e.g., in-order traversal or pre-order traversal)

To achieve this module’s objectives, complete the following:

Read: Essential Algorithms pp. 7–19, 227–233, 237–240, 242–244

Read / view the following content and complete any comprehension checks:

• Complexity, continued
• Trees
• Representing trees
• Depth-first search
• Breadth-first search
• Expression trees

Project 2

If you haven’t already started, please start work on project 2.

Original author: Clayton Cafiero < [given name] DOT [surname] AT uvm DOT edu >

No generative AI was used in producing this material. This was written the old-fashioned way.

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