A structured outline of the module's core topics — covering binary tree fundamentals (nodes, edges, root), tree anatomy, BST ordering and node structure, insertion and search logic with JavaScript implementation, and tree traversal methods — used by learners to preview what will be taught and by instructors to verify full curriculum coverage.
Module Artifacts — 9 items
This reading introduces the definition, terminology (root, parent, child, leaf), and structural rules of binary trees, giving learners the conceptual foundation needed before studying algorithms or specialized tree variants.
This reading explains the anatomy of a binary tree at the node level — covering pointer structure, left/right child relationships, and how nodes link together — so learners can reason precisely about tree construction and manipulation.
This reading defines the Binary Search Tree ordering property (left subtree holds smaller values, right holds larger), distinguishing BSTs from general binary trees, so learners understand the invariant that makes BST operations efficient.
This reading walks through how insertion and search operations work in a BST by following the ordering invariant at each node, helping learners understand the recursive logic and efficiency of these two core operations.
This reading covers the three cases of BST node deletion — leaf node, one-child node, and two-child node (using in-order successor/predecessor) — so learners understand how to remove nodes without violating the BST ordering property.
This reading surveys tree traversal strategies — including in-order, pre-order, post-order, and level-order — explaining the visit sequence each produces and when each strategy is appropriate for a given task.
This reading guides learners through a complete from-scratch JavaScript implementation of a BST, including class and node structure and recursive algorithms, so they can translate conceptual BST knowledge into working code.
This reading guides learners through a complete from-scratch JavaScript implementation of a BST, including class and node structure and recursive algorithms, so they can translate conceptual BST knowledge into working code.