🚀 Efficient Coding Spotlight: Counting Negatives in a Grid with Binary Search! Recently, I tackled an interesting problem: Count the number of negative numbers in a sorted 2D grid. While a brute-force approach works, I wanted something faster and more elegant. Here’s how I combined the power of binary search with 2D arrays in Java: Leetcode problem: https://lnkd.in/gcfH37k2 What’s cool about this approach? ⚡ Optimized Performance: By leveraging binary search on each row, the time complexity is reduced from O(mn) to O(mlog n). 🤖 Algorithmic Thinking: Instead of scanning every cell, find the first negative in each row and quickly calculate the count. 💡 Scalable: Perfect for large datasets where efficiency is key. Takeaway: Sometimes, a classic algorithm like binary search can offer a huge speed boost in unexpected places. #Java #Algorithms #Coding #BinarySearch #Programming #TechTips
Monotonic also another approach
Thodupunuri Saipriya presents a comprehensive methodology to effectively address the issue at hand.
when i read the problem first i knew an o(m*n) brute force can solve the it but since the array is sorted i went ahead for a binary search solution that lead to o(n*logm) in worst case, then after reading analyzing and doing dry runs i realized that the stair case approach works because there is a diagonal like boundary between positives and negatives and we only need to traverse that boundary ---------------------------------------------- i have also built a visualizer for this problem , do check it out here->https://www.garudax.id/posts/dushyant-hada_dsa-leetcode-reactjs-ugcPost-7411261824806969344-wo4A?utm_source=share&utm_medium=member_desktop&rcm=ACoAAF9GdyYBpdfbKFAbZhYFLrT9tI_IkLf_LWM