Jobs
Interviews

Solve Count Limited Range Subsequences using JavaScript Language

Solve Count Limited Range Subsequences using JavaScript to enhance your skills with javascript coding practice , master coding concepts, and prepare for interviews with practical exercises and detailed solutions.

Count Limited Range Subsequences

Difficulty : Hard

Categories :

  • Arrays

You are given an array of integers arr and an integer k. Your task is to find the number of subsequences in the array where:

  • The subsequence length is exactly k
  • The difference between the maximum and minimum elements in the subsequence is at most 2

Return the count of such subsequences.

Constraints:

  • 1 ≤ k ≤ arr.length ≤ 1000
  • 1 ≤ arr[i] ≤ 100
  • The answer will be less than 2^31

Examples:

Input: arr = [3,1,4,1,5], k = 2
Output: 3
Explanation: Valid subsequences are: [1,1], [3,4], [4,5]
Note that [1,5] is not valid as 5-1 > 2
Input: arr = [1,1,1,2,2], k = 2
Output: 10
Explanation: All possible subsequences of length 2 are valid as max difference is at most 1

Problem Solving

Input

What You'll Find Here

Hands-On Exercises Work on coding problems inspired by real-world scenarios.

Detailed Explanations Break down complex solutions into easy-to-understand steps.

Interactive Learning Test your skills in an engaging and fun way.

Choose from the following categories

Strings A sequence of characters used to represent text, with problems focused on manipulation, searching, and pattern matching.

Arrays A collection of elements stored in contiguous memory locations, allowing efficient random access and manipulation.

Linked Lists A linear data structure where each element (node) points to the next, offering dynamic memory allocation and efficient insertions/deletions.

Trees A hierarchical data structure with nodes connected by edges, used in applications like databases, file systems, and parsing.

Graphs A collection of nodes (vertices) connected by edges, representing relationships, widely used in networking, routing, and social networks.

Dynamic Programming An optimization technique that solves problems by breaking them into overlapping subproblems and storing their results.

Backtracking A problem-solving method that explores all possibilities recursively, backtracking when a solution is not feasible.

Sorting Algorithms Techniques for arranging elements in a specific order, such as quicksort, mergesort, and bubble sort, essential for data organization.

Searching Algorithms Methods for finding elements in a dataset, such as binary search, linear search, and graph traversal techniques.

Mathematics A field of study involving numbers, calculations, and logical reasoning, forming the foundation for algorithms and problem-solving.

Recursion A programming technique where a function calls itself to solve smaller instances of the same problem, often used in divide-and-conquer approaches.

Bit Manipulation Operations performed directly on binary representations of data, used for efficient computations and optimization tasks.