We are building an in-memory session cache for an API gateway handling 50k requests/sec. We need an LRU (Least Recently Used) cache where both get() and put() operations happen strictly in O(1) time. A lot of implementations I see online either ...Read more
I understand how to solve the Largest Rectangle in Histogram in O(N^2) by expanding left and right from every bar. But top interviewers and competitive programming platforms always expect the O(N) single-pass Monotonic Stack solution. Every explanation I read online just ...Read more
When implementing Dijkstra’s algorithm for large road networks (millions of nodes and edges), the standard textbook approach pushes a new pair (new_dist, u) into a binary heap whenever a shorter path is found. This means old, obsolete distance pairs remain sitting ...Read more
In our embedded C++ runtime, each thread has a strictly limited stack frame (64KB). When traversing deeply skewed binary trees with millions of nodes, recursive DFS triggers a stack overflow, and allocating an explicit heap stack (std::vector) exceeds our device ...Read more
In standard textbook explanations of the 0/1 Knapsack problem, the solution uses a 2D table dp[n][W] where each cell represents the max value using a subset of items under capacity W. Then instructors show an optimization: ‘Just replace the 2D array ...Read more
The standard DP solution for Longest Increasing Subsequence (LIS) uses two nested loops: for each element i, scan all previous elements j < i. That takes O(N^2) time, which times out when N = 100,000. Everyone says the optimal solution is ...Read more