DSA · Theory

Self-Balancing Binary Search Trees

Theory

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Self-Balancing Binary Search Trees

Self-Balancing Binary Search Trees is simple if you keep it on paper. Meera uses it for folder on disk in a file explorer.

Self-Balancing Binary Search Trees order: meaning → left < root < right → one limit. Dumping ten features helps nobody.

Without Self-Balancing Binary Search Trees, a file explorer gets messy and folder on disk is hard to trust.

Use Self-Balancing Binary Search Trees when folder on disk must stay clear. If a simpler DSA step works, use that instead.

Self-Balancing Binary Search Trees trap — unbalanced BST becoming a list. Meera loses marks for that every viva.

After Self-Balancing Binary Search Trees, Meera should still remember unbalanced BST becoming a list.

Close Self-Balancing Binary Search Trees with: “If I skip it, folder on disk goes wrong like this: unbalanced BST becoming a list.”

Diagram

Exam tip

For Self-Balancing Binary Search Trees: definition + a file explorer + one failure.

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))

Self-Balancing Binary Search Trees — binary search halves a sorted array each step — O(log n).

Short notes

DefSelf-Balancing Binary Search Trees — Meera uses it for folder on disk in a file explorer.
RuleSelf-Balancing Binary Search Trees → left < root < right.
RememberSelf-Balancing Binary Search Trees + a dry-run table (a file explorer).
UseSelf-Balancing Binary Search Trees in a file explorer (folder on disk).
TrapSelf-Balancing Binary Search Trees — unbalanced BST becoming a list.
ExSelf-Balancing Binary Search Trees → 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))

Self-Balancing Binary Search Trees

Example

Short notes

Questions

Self-Balancing Binary Search Trees

Example

Short notes

Questions