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How to handle duplicates in Binary Search Tree

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How to handle duplicates in Binary Search Tree

How to handle duplicates in Binary Search Tree is simple if you keep it on paper. Priya uses it for folder on disk in a file explorer.

How to handle duplicates in Binary Search Tree order: meaning → left < root < right → one limit. Dumping ten features helps nobody.

How to handle duplicates in Binary Search Tree exists so Priya can keep folder on disk correct in a file explorer.

How to handle duplicates in Binary Search Tree shows up in a file explorer. Name folder on disk, not “a real-world scenario”.

How to handle duplicates in Binary Search Tree trap: unbalanced BST becoming a list. Priya loses marks for that every viva.

After How to handle duplicates in Binary Search Tree, Priya should still remember unbalanced BST becoming a list.

Close How to handle duplicates in Binary Search Tree with: “If I skip it, folder on disk goes wrong like this: unbalanced BST becoming a list.”

Diagram

Exam tip

Say How to handle duplicates in Binary Search Tree in one breath, then left < root < right, then 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))

How to handle duplicates in Binary Search Tree — binary search halves a sorted array each step — O(log n).

Short notes

DefHow to handle duplicates in Binary Search Tree — Priya uses it for folder on disk in a file explorer.
RuleHow to handle duplicates in Binary Search Tree → left < root < right.
RememberHow to handle duplicates in Binary Search Tree + a dry-run table (a file explorer).
UseHow to handle duplicates in Binary Search Tree in a file explorer (folder on disk).
TrapHow to handle duplicates in Binary Search Tree — unbalanced BST becoming a list.
ExHow to handle duplicates 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))

How to handle duplicates in Binary Search Tree

Example

Short notes

Questions

How to handle duplicates in Binary Search Tree

Example

Short notes

Questions