Step 14: Binary Search Trees [Concept and Problems]›Practice Problems
Floor in a Binary Search Tree
EasyFunction: floorInABinarySearchTree()
ASCI Mission Breakdown • Simple as Hell
"Master Floor in a Binary Search Tree: Take `nums` (number[]) and `target` (number), execute an optimal practice problems strategy, and return number with clean edge-case handling."
Real-World Metaphor:
Think of Floor in a Binary Search Tree as an everyday real-world challenge: you receive input data, inspect its elements in sequence without making unnecessary duplicate passes, and transform the collection to reach the exact target without wasting computer memory.
Interactive Visual WalkthroughBINARY-TREE
Step 1 / 3
StatusInitialized
ModeScanning
Evaluating
1. Initialize State for Floor in a Binary Search Tree
Load inputs and initialize algorithmic registers.
How to Think About This (Mental Model)
Unpack the problem parameters (`nums` (number[]) and `target` (number)) and clarify what is given vs what must be returned.
Identify the optimal data structure or pattern (e.g. pointers, hash map, or stack) to avoid redundant recalculations.
Walk through state transitions, handle edge cases (empty collections, single items, negative numbers), and return the verified result.
Given a sorted array of integers `nums` and an integer `target`, find the index or answer corresponding to **Floor in a Binary Search Tree**.
Your solution must achieve logarithmic runtime complexity `O(log N)`.
Examples
Example 1
Input: nums = [1,3,5,6], target = 5
Output: 2
Explanation: 5 is found at index 2.
Example 2
Input: nums = [1,3,5,6], target = 2
Output: -1
Explanation: 2 is not present in the array.
Constraints
1 <= nums.length <= 10^5
-10^9 <= nums[i], target <= 10^9
Topic Tags:
Binary Search Trees [Concept and Problems]Practice ProblemsfloorInABinarySearchTree