Dynamic Programming (DP) is an algorithmic technique for solving complex problems by breaking them down into smaller, overlapping subproblems and storing their results to avoid redundant calculations. Why do we even need dynamic programming? Before DP, let’s understand the problem DP is solving. The Core Problem Many problems: This leads to: Example: Fibonacci Subproblems For … Read more
Many brute-force solutions run in O(N²) or worse, which is unacceptable for large inputs. The Sliding Window technique is one of the most powerful ways to cut down unnecessary work and bring solutions down to O(N) or O(N log N). If you’ve ever solved problems around subarrays, substrings, or continuous segments, chances are you’ve already … Read more
Apache Kafka has become the backbone of modern real-time data pipelines and event-driven architectures. Originally developed at LinkedIn and later open-sourced, Kafka is now one of the most widely adopted distributed streaming platforms. It is designed to handle high-throughput, fault-tolerant, and scalable event streaming across diverse industries. What is Kafka? At its core, Kafka is … Read more
Let’s go deep into Prefix Sum (Pre Sum) from a competitive programming perspective.This is one of the fundamental techniques you’ll repeatedly use in array, string, DP, and number theory problems. What is Prefix Sum? For an array arr[0..n-1], the prefix sum array pre[i] is defined as: That is, the cumulative sum up to index i. … Read more
The two pointer technique is one of the most common and powerful patterns used in competitive programming, data structures, and algorithms. It helps solve problems that involve searching, sorting, or traversing arrays, strings, or linked lists in an efficient way. Core The Two Pointers pattern is a common algorithmic technique used primarily to simplify problems … Read more
Greedy algorithms are one of the most elegant problem-solving strategies in computer science. They are fast, intuitive, and often surprisingly effective—but only when applied to the right problems. This guide walks you through the recipe for designing greedy algorithms, the common proof techniques, and the classic patterns you must know. What Is a Greedy Algorithm? … Read more
A Queue is a linear data structure that follows the principle of First In, First Out (FIFO). Introduction A Queue is a linear data structure that follows the principle of First In, First Out (FIFO). This means that the first element inserted into the queue will be the first one to be removed — just … Read more
Tree traversals are one of the first things we learn in data structures — but they’re often taught only at a surface level: as different ways to “walk” a tree. What’s rarely emphasized is this: A Quick Refresher Given a binary tree, the three primary depth-first traversals are: Traversal Order Preorder Root → Left → … Read more
Check Same binary Tree Leet 100. Same Tree When we first read the “Same Tree” problem, we often think of comparing the traversal results — like inorder, preorder, or postorder — of both trees. That’s a natural and valid idea, but it’s not necessary or ideal in this case. Case 1 : Using one of … Read more