DSA · Theory

Binary Search Tree vs Ternary Search Tree

Theory

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Binary Search Tree vs Ternary Search Tree

Don’t start Binary Search Tree vs Ternary Search Tree with jargon. Start with folder on disk. That is the whole point.

Do Binary Search Tree vs Ternary Search Tree once by hand. left < root < right. Change one input. Say the new result out loud.

Without Binary Search Tree vs Ternary Search Tree, a file explorer gets messy and folder on disk is hard to trust.

Rohit ships Binary Search Tree vs Ternary Search Tree in a file explorer. That is the use case worth saying.

Don’t do this with Binary Search Tree vs Ternary Search Tree: unbalanced BST becoming a list. Interviewers spot it in ten seconds.

After Binary Search Tree vs Ternary Search Tree, Rohit should still remember unbalanced BST becoming a list.

One breath for Binary Search Tree vs Ternary Search Tree, then folder on disk, then unbalanced BST becoming a list. Sit down.

Diagram

Exam tip

Board: folder on disk. Dry-run Binary Search Tree vs Ternary Search Tree. Name the trap: unbalanced BST becoming a list.

Example

def binary_search(arr, target):
    lo, hi = 0, len(arr) - 1
    while lo <= hi:
        mid = (lo + hi) // 2
        if arr[mid] == target:
            return mid
        if arr[mid] < target:
            lo = mid + 1
        else:
            hi = mid - 1
    return -1

print(binary_search([1, 3, 5, 7, 9], 7))

Binary Search Tree vs Ternary Search Tree — binary search halves a sorted array each step — O(log n).

Short notes

DefBinary Search Tree vs Ternary Search Tree — Rohit uses it for folder on disk in a file explorer.
RuleBinary Search Tree vs Ternary Search Tree → left < root < right.
RememberBinary Search Tree vs Ternary Search Tree + Big-O (a file explorer).
UseBinary Search Tree vs Ternary Search Tree in a file explorer (folder on disk).
TrapBinary Search Tree vs Ternary Search Tree — unbalanced BST becoming a list.
ExBinary Search Tree vs Ternary Search Tree → folder on disk.

def binary_search(arr, target): lo, hi = 0, len(arr) - 1 while lo <= hi: mid = (lo + hi) // 2 if arr[mid] == target: return mid if arr[mid] < target: lo = mid + 1 else: hi = mid - 1 return -1 print(binary_search([1, 3, 5, 7, 9], 7))

Binary Search Tree vs Ternary Search Tree

Example

Short notes

Questions

Binary Search Tree vs Ternary Search Tree

Example

Short notes

Questions