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Practice Problems

Practice Problems on Binary Search Tree (BST)​

Binary Search Trees (BSTs) are a fundamental data structure in computer science. They allow for efficient searching, insertion, and deletion of elements. Here’s a collection of practice problems that will help you master the various aspects of working with Binary Search Trees. The problems are grouped by difficulty, enabling you to build your skills progressively.

Basic Problems:​

These problems will introduce you to basic Binary Search Tree operations and properties. They are ideal for beginners who are just getting started with BSTs.

  • Convert Sorted Array to Binary Search Tree:
    Convert a sorted array into a height-balanced binary search tree, practicing the conversion of linear data structures into trees.

  • Closest Binary Search Tree Value:
    Find the closest value in a BST to a given target value. This problem tests your ability to navigate the tree structure efficiently.

  • Find Mode in Binary Search Tree:
    Find the mode (most frequent value) in a BST. The problem tests traversal methods and counting techniques.

  • Minimum Absolute Difference in BST:
    Find the minimum absolute difference between values of any two nodes in a BST. This is a good problem to practice in-order traversal.

  • Two Sum IV - Input is a BST:
    Given a target value, determine if there exist two elements in a BST that sum up to the target. This problem combines BST traversal with the two-sum technique.

Intermediate Problems:​

These problems require a deeper understanding of BST properties and involve more complex operations such as tree generation, validation, and modifications.

  • Unique Binary Search Trees II:
    Generate all structurally unique BSTs that store values from 1 to n. This problem tests your ability to generate trees recursively.

  • Unique Binary Search Trees:
    Calculate the number of unique BSTs that can be formed with n nodes. This is an exercise in understanding tree permutations and combinatorics.

  • Validate Binary Search Tree:
    Validate if a given binary tree is a valid BST. This is a fundamental problem to test your understanding of the BST property.

  • Recover Binary Search Tree:
    Given a BST where two nodes are swapped by mistake, recover the tree without modifying its structure. This problem requires careful analysis of in-order traversal.

  • Convert Sorted List to Binary Search Tree:
    Convert a sorted linked list into a height-balanced BST. This problem combines list manipulation with tree generation.

Advanced Problems:​

These problems require advanced techniques and a solid understanding of BST operations. They often involve more than one data structure or sophisticated operations.

  • Two Sum BSTs:
    Given two binary search trees, determine if there exist two elements (one from each tree) that add up to a target value.

  • Balance a Binary Search Tree:
    Convert an unbalanced BST into a balanced BST while maintaining its elements' order.

  • All Elements in Two Binary Search Trees:
    Return all elements from two BSTs in sorted order. This problem requires merging two trees and producing sorted output efficiently.

  • Binary Search Tree Iterator II:
    Implement an iterator over a binary search tree (BST) that supports the next(), hasNext(), prev(), and hasPrev() operations.

  • Depth of BST Given Insertion Order:
    Given the insertion order of a BST, calculate the depth of the resulting tree. This problem explores the relationship between insertion order and tree depth.

Challenges:​

These problems are for those looking for extra challenges that test edge cases or involve difficult operations on BSTs.

These problems will help you develop a strong understanding of Binary Search Trees, a crucial data structure in many algorithmic problems. Happy coding!