LeetCode Problem: Subarray Sum Equals K | Prefix Sum + HashMap Solution in C#

Here's my optimized solution to the LeetCode Problem: Subarray Sum Equals K, implemented in C# using Prefix Sum and a HashMap for efficient computation. 🚀

💡 Problem Overview:
This problem requires finding the total number of continuous subarrays in an array that sum up to a given value k. Using a combination of Prefix Sum and HashMap, this solution efficiently tracks cumulative sums and their occurrences, reducing both time and space complexity.

✅ What You'll Learn in This Video:

The concept of Prefix Sum and how it simplifies subarray sum calculations.
How to use a HashMap (Dictionary) to store cumulative sums and quickly count valid subarrays.
A clean and efficient implementation that's easy to follow, explained step-by-step.
🔔 Highlights of This Solution:

Time Complexity: O(n), as the array is traversed once, and HashMap operations (insertions and lookups) run in constant time on average.
Space Complexity: O(n), as the HashMap stores prefix sums for up to n elements in the worst case.
Core Insight: Using a Prefix Sum and hashmap to avoid nested loops allows us to calculate subarray sums in linear time, making this approach significantly faster than brute force methods.
💡 Whether you're preparing for coding interviews or improving problem-solving skills for array-based challenges, this tutorial provides the concepts and techniques to solve related problems efficiently.

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Видео LeetCode Problem: Subarray Sum Equals K | Prefix Sum + HashMap Solution in C# канала TechWithRohith