Knapsack derives its name from the problem faced by someone who is constrained by a fixed-size knapsack and must fill it with the most valuable items. The problem often arises in resource allocation, where decision-makers must choose from a set of indivisible projects or tasks under a fixed budget or time constraint, respectively. What is … Read full article: Knapsack — The Master DP Pattern
Dynamic Programming (DP) is an optimisation technique that solves complex problems by breaking them down into smaller, overlapping subproblems and storing their results to avoid redundant calculations. About DP Why do we even need dynamic programming? Before DP, let’s understand the problem DP is solving. While solving a problem, we often end up solving the … Read full article: Dynamic Programming (DP): A Complete Guide
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 full article: Mastering the Sliding Window Technique
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 full article: Apache Kafka: A Complete Guide
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 full article: Prefix Sum (Pre Sum) in Competitive Programming
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 full article: The Two Pointer Technique: A Complete Guide
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 full article: Mastering Greedy Algorithms
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 full article: Queue: A Detailed Guide
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 full article: The Deep Power Behind Tree Traversals: Preorder, Inorder, Postorder