DSA · Theory

Floor and Ceiling in Binary Search Tree

Theory

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Floor and Ceiling in Binary Search Tree

Floor and Ceiling in Binary Search Tree sits in a file explorer. Dev’s job is folder on disk. Write that first.

Keep Floor and Ceiling in Binary Search Tree small. Dev should finish folder on disk in a few lines, not a 40-line dump.

Floor and Ceiling in Binary Search Tree exists so Dev can keep folder on disk correct in a file explorer.

Dev ships Floor and Ceiling in Binary Search Tree in a file explorer. That is the use case worth saying.

Floor and Ceiling in Binary Search Tree miss: unbalanced BST becoming a list. Fix it before you talk about advanced DSA.

After Floor and Ceiling in Binary Search Tree, Dev should still remember unbalanced BST becoming a list.

Viva for Floor and Ceiling in Binary Search Tree: what it is → left < root < right → the mistake (unbalanced BST becoming a list).

Diagram

Exam tip

Board: folder on disk. Dry-run Floor and Ceiling in Binary 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))

Floor and Ceiling in Binary Search Tree — binary search halves a sorted array each step — O(log n).

Short notes

DefFloor and Ceiling in Binary Search Tree — Dev uses it for folder on disk in a file explorer.
RuleFloor and Ceiling in Binary Search Tree → left < root < right.
RememberFloor and Ceiling in Binary Search Tree + Big-O (a file explorer).
UseFloor and Ceiling in Binary Search Tree in a file explorer (folder on disk).
TrapFloor and Ceiling in Binary Search Tree — unbalanced BST becoming a list.
ExFloor and Ceiling in Binary 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))

Floor and Ceiling in Binary Search Tree

Example

Short notes

Questions

Floor and Ceiling in Binary Search Tree

Example

Short notes

Questions