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Solve Sliding Window Maximum using Rust Language

Solve Sliding Window Maximum using Rust to enhance your skills with rust coding practice , master coding concepts, and prepare for interviews with practical exercises and detailed solutions.

Sliding Window Maximum

Difficulty : Medium

Categories :

  • Arrays

Given an array of integers and a window size k, find the maximum element in each sliding window of size k as it moves from left to right. Return an array of maximum elements for each window position.

Constraints:

  • 1 ≤ arr.length ≤ 10⁵
  • 1 ≤ k ≤ arr.length
  • -10⁴ ≤ arr[i] ≤ 10⁴

Examples:

Input:
arr = [1,3,-1,-3,5,3,6,7], k = 3
Output: [3,3,5,5,6,7]
Explanation:
Window [1,3,-1] -> max = 3
Window [3,-1,-3] -> max = 3
Window [−1,−3,5] -> max = 5
Window [-3,5,3] -> max = 5
Window [5,3,6] -> max = 6
Window [3,6,7] -> max = 7
Input:
arr = [1,-1], k = 1
Output: [1,-1]
Explanation:
Each element is max in its single-element window

Problem Solving

Input

What You'll Find Here

Real-World Challenges Solve problems that help you master Rust's unique features.

Detailed Explanations Break down complex concepts into manageable steps.

Industry-Ready Skills Prepare for systems programming and performance-critical applications.

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.