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• Data Structures and Algorithms (DSA) Patterns: A Structured Approach to Problem SolvingJul 07, 2026. Master DSA patterns for efficient problem-solving, interview success, and scalable software design. Unlock your coding potential!
• Recursion & Algorithms in C#Oct 29, 2025. Explore recursion and algorithms in C# with a practical factorial example using WebForms. Learn how to implement recursive functions and understand their advantages and disadvantages. A clear guide with code!
• Chapter 16: STL: Iterators and Algorithms in C++Oct 23, 2025. Unlock the power of C++ STL! Master iterators for traversing containers and algorithms for data manipulation. Includes sorting, finding, reversing, and lambda functions.
• How to Convert Recursive Algorithms to Iterative in JavaSep 23, 2025. Avoid StackOverflowError in Java by converting recursive algorithms to iterative solutions. Learn how to transform tail recursion into loops, simulate recursion with stacks for DFS, use dynamic programming for overlapping subproblems like Fibonacci, and leverage queues for BFS. Optimize performance and memory usage by choosing iteration over recursion when depth is a concern. This guide provides practical Java code examples for each conversion strategy, ensuring robust and efficient code.
• Best Ways to Learn Data Structures and Algorithms EffectivelySep 23, 2025. This article provides a clear path for beginners, covering essential concepts like Big-O notation, arrays, and linked lists. Learn through coding platforms, books, and visualization tools. Practice problem-solving patterns, participate in competitions, revise regularly, and apply DSA in real projects to become a confident programmer and excel in coding interviews.
• What is Data Structures and Algorithms (DSA), and why is it important?Sep 03, 2025. Unlock the power of Data Structures and Algorithms (DSA)! This guide breaks down DSA, explaining how it's fundamental to efficient coding and problem-solving. Learn about arrays, linked lists, sorting, searching, and why mastering DSA is crucial for coding interviews, real-world applications, and a successful career in computer science. Discover how DSA drives Google Search, navigation apps, and e-commerce platforms.
• Data Structures and Algorithms CheatsheetAug 26, 2025. A complete DSA cheatsheet covering arrays, linked lists, stacks, queues, trees, graphs, sorting, searching, recursion, dynamic programming, and key algorithms with Python examples for quick revision.
• Master C# from Basics to Advanced | Complete C# Learning Path with Algorithms & Real-World SkillsAug 17, 2025. Learn C# step by step! From basics to advanced concepts with 20+ algorithms, OOP, LINQ, async, desktop & web app development.
• Top Algorithms in Supervised vs. Unsupervised LearningAug 02, 2025. Explore the leading supervised and unsupervised machine learning algorithms, their strengths, and real-world applications. Learn when to pick decision trees, neural networks, K-Means, PCA, and more to tackle your data challenges effectively.
• Optimizing Searching Algorithms in C# and Reducing ComplexitiesAug 30, 2024. This article explores the implementation of 10 common searching algorithms in C#, detailing their use cases, workings, and complexities. From simple linear searches to more complex algorithms like Binary Search, Jump Search, and KMP, this guide provides code examples and insights into optimizing search efficiency.
• Data Structures and Algorithms (DSA) using C# .NET Core — Binary Trees and Binary Tree Types IIJul 29, 2024. This article explores various types of binary trees, including Full, Perfect, Complete, Balanced, Skewed, and Degenerate Binary Trees. It explains their properties and distinctions, such as how Full and Perfect trees differ from Complete trees.
• Rate Limiting Algorithms in .NET CoreJan 24, 2024. We’ll explore various rate limiting algorithms in the context of .NET Core, providing code snippets for implementing Token Bucket, Sliding Window, Fixed Window, and Concurrency limiters.
• Data Structures and Algorithms (DSA) using C# .NET Core - Binary Trees and Binary Search Tree (BST) Tree Traversal- IIJan 02, 2024. The fundamentals of Tree and Binary Search Tree, delving into data reading, node addition, deletion, and search operations through tree traversal. Understand three traversal types: Preorder, Inorder, and Postorder. Source code included.
• Data Structures and Algorithms (DSA) using C# .NET Core — Binary Trees and Binary Search Tree (BST) - INov 27, 2023. In this article we will learn about - Binary Trees. Explore the fundamentals of trees and delve into binary trees, focusing on Binary Search Trees (BST). Understand key terminologies, tree traversal, and mathematical formulas for node calculations in this comprehensive guide.
• Understanding Consensus Algorithms In BlockchainFeb 03, 2023. In this article, we'll go through some of the popular consensus algorithms currently being used by different blockchains, including.
• Learn About Data Structures And Algorithms (DSA)Nov 13, 2018. This article will tell you almost everything about the crucial concepts of data structures and algorithms. This article is the first one in the series of “Data Structure and Algorithm (DSA)”. You’ll learn more about data structures and algorithms in details in my coming articles. So stay tuned for next articles.
• Implement Symmetric And Asymmetric Cryptography Algorithms With C#Dec 09, 2017. How to encrypt and decrypt data using Symmetric and Asymmetric algorithms using C# Programming language
• Data Structures And Algorithms - Part Three - An Array Of FunJun 15, 2017. Arrays in computer science are static data structures that store elements in contiguous memory locations. They can be one-dimensional, two-dimensional, or jagged arrays. This article explores how to declare, manipulate, and use arrays in C#, along with algorithmic considerations like time complexity.
• Data Structures And Algorithms - Part Two - A Word About Big-O NotationMay 22, 2017. This article is an introduction to Big-O Notation, which is used to measure the running time of a function/ method.
• Introduction To AES And DES Encryption Algorithms In .NETFeb 17, 2017. Explore encryption methods like Symmetric (DES, 3DES, AES) and Asymmetric (RSA, DSA), highlighting key differences in key management, security, and performance. Understand DES vulnerabilities and advancements in AES. Learn about RSA, DSA, and their significance in secure data transmission.
• Regression Algorithms Parameters In Azure MLMay 07, 2016. In this article you will learn about Regression Algorithms parameters in Azure ML.
• Classification Algorithms Parameters In Azure MLApr 25, 2016. In this article you will learn about Classification Algorithms parameters in Azure ML.
• Understanding Classification Algorithms In Azure MLApr 25, 2016. In this article you will understand about Classification Algorithms in Azure ML.
• A Day Without Visual Studio; Game Programming Algorithms and Techniques ReviewJan 09, 2015. This article provides a brief Game Programming Algorithms and Techniques book review.
• Genetic Algorithms in .NETDec 15, 2010. Genetic Algorithms (GAs) are adaptive methods that can be used to solve search and optimization problems.
• Using Symmetric Algorithms to Encrypt DataMay 20, 2008. In this article, I will propose a method of how to encrypt data and store it using symmetric algorithms whose are, in fact, four integrated classes within the .Net framework, namely DES,RC2,Rijndael and TripleDES but I will perform the task using the two last ones as they are the mostly used in real time cases.
• Using Genetic Algorithms to Determine Calculus Derivative Functions in C# and.NETNov 28, 2006. This article describes how you can use genetic algorithms in .NET to determine derivatives of mathematical functions. The program uses an algorithm called Multiple Expression Programming (MEP) inside the genomes to exercise a function tree.
• Solving Polynomial Equations with Complex Roots using Genetic Algorithms in C#Apr 09, 2006. This article features a program in which the user can enter a polynomial equation and it will use GAs to determine the complex roots.
• AI: Using Genetic Algorithms and NetSpell to Solve AnagramsMar 27, 2006. Remember the puzzles where you are given a jumble of letters and you have to unscramble a word? This article shows you how to use a genetic algorithm and NetSpell, an open source spell checker, to solve these anagram puzzles.
• Using Genetic Algorithms to come up with Sudoku PuzzlesSep 23, 2005. Sudoku is a new type of puzzle from Japan that will keep you entertained for a time and may even get you hooked. This article demonstrates how to generate a fully populated Sudoku grid using genetic algorithms.
• Evolving Numeric Series using Genetic Algorithms in C#Jul 27, 2004. If you ever browsed around the book store, you'll notice these puzzle books or IQ test books and some of the books contain questions asking you to complete a series of numbers.
• Evolving Register Network using Genetic Algorithms in C# Jun 23, 2004. Genetic Algorithms are powerful AI tools because they can evolve through trial and error and converge into a solution. In this article we will use genetic algorithms to come up with an analog solution.
• Using Genetic Algorithms to Generate Evolutionary Art in C# and .NETOct 10, 2003. In this article we will experiment a bit with genetic algorithms and creating fitness functions that produce art on a Windows Form.
• Using Generic Algorithms to Layout Circuit BoardsApr 07, 2003. This article tells you how to use a Genetic Algorithm to optimally layout parts on a circuit board so they have the shortest connections between them.
• Using Genetic Algorithms to Design Logic Circuits in C#Feb 05, 2003. The article goes to explain that GA (Genetic Algorithms) have been used by various programmers to come up with 15 previous patented inventions + (and here is the startling part) some new ones! I can see the running joke in the patent office now.
• Mastermind Computer Player using Genetic Algorithms in C#Jul 22, 2002. After writing the Genetic Algorithm Article for implementing a Genetic Algorithm in C#, I tried to think of a good example of how to illustrate a real-world use of Genetic Algorithms to illustrate artificial intelligence.
• Implementing a Genetic Algorithms in C# and .NETApr 14, 2002. One of the more interesting developments that has come out of the Artificial Intelligence world is the invention of Genetic Algorithms.
• AI-Powered File Summarizer: Deep-Dive Architecture, Algorithms, Workflows, and Enterprise IntegrationNov 14, 2025. Comprehensive, SEO- and GEO-optimized guide to AI-powered file summarizers, covering full architecture, algorithms, RAG pipelines, extraction methods, implementation code, enterprise workflows, use cases, limitations, and optimization techniques.
• Understanding Searching Algorithms: Linear Search and Binary SearchOct 14, 2025. Explore the fundamentals of searching algorithms with Linear and Binary Search. Learn how these algorithms efficiently locate elements within data structures. Discover their step-by-step logic, Python implementations, and time/space complexity. Understand when to use each algorithm based on data characteristics and performance needs. Master these essential techniques for efficient data retrieval in programming and real-world applications. Binary search is faster but requires sorted data.
• Understanding Sorting Algorithms: Bubble, Merge, and Quick SortOct 13, 2025. Explore fundamental sorting algorithms: Bubble Sort, Merge Sort, and Quick Sort. Learn how these algorithms arrange data for efficient searching and processing. Understand their time and space complexities, advantages, and disadvantages. Discover real-world applications in databases, search, and machine learning. Choose the right algorithm for optimized performance and efficient data management.
• What is Graph Algorithms: BFS, DFS, and Shortest Path with ExamplesOct 12, 2025. Explore graph algorithms like BFS, DFS, and Dijkstra's for efficient problem-solving. Learn how BFS finds shortest paths in unweighted graphs, DFS excels in cycle detection, and Dijkstra's optimizes routes in weighted graphs. Discover real-world applications in navigation, social networks, and AI, mastering essential tools for connectivity, optimization, and exploration in computer science. These algorithms are crucial for developers tackling complex challenges.
• What is the Difference Between Data Structures and Algorithms?Sep 23, 2025. Discover the difference between data structures and algorithms with clear definitions, detailed examples, comparison tables, and real-world use cases. Learn why both are essential for coding, interviews, and software development in the US, UK, and India.
• How Can Blockchain Systems Migrate to Quantum-Resistant Algorithms? 🔐⚛️Aug 29, 2025. Explore blockchain's quantum threat & migration to quantum-resistant algorithms (PQC). Learn strategies, challenges, and a roadmap for a secure future.
• AI in Education: Personalized Learning with Smart AlgorithmsAug 27, 2025. AI is transforming education through personalized learning, adapting lessons to each student’s pace, strengths, and needs. With smart algorithms, it enhances engagement, feedback, and overall learning outcomes.
• Generative AI: Creating Content with Smart AlgorithmsAug 19, 2025. Generative AI creates new content from text, images, music, and 3D designs using models like GANs and transformers. It boosts creativity, personalization, and efficiency across industries while raising ethical and bias concerns.
• Validate Binary Search Tree in DSA – Rules, Algorithms, and CodeAug 13, 2025. Learn how to validate whether a given binary tree is a valid Binary Search Tree (BST) using step-by-step logic, rules, iterative and recursive algorithms, and Java examples.
• Dynamic Pricing in E-Commerce: Maximizing Revenue with C# AlgorithmsDec 23, 2024. Dynamic pricing allows businesses to adjust product prices in real time based on factors like demand, competition, and inventory levels. This article explains dynamic pricing, its benefits, and a basic C# implementation of a pricing algorithm.
• Arrays in Data Structures and AlgorithmsApr 11, 2024. Arrays are essential data structures in programming, storing similar data items in contiguous memory. They streamline organization and access, enabling efficient storage and retrieval of elements and simplifying coding tasks effectively.
• Hashing Techniques in Data Structures and AlgorithmsMar 20, 2024. Hashing in data structures utilizes hash functions to map arbitrary-sized data to fixed-size values, enabling efficient storage and retrieval within large datasets commonly employed in hash tables and maps.
• Algorithms And Data Structures Interview Question - RecursionDec 01, 2022. In this article, you will learn about algorithms and data structures interview question - recursion.
• Knapsack Problem In Analysis And Design Of AlgorithmsSep 04, 2020. In this article, you will learn about the Knapsack problem in the analysis and design of algorithms.
• How To Choose Machine Learning AlgorithmsJul 10, 2019. In this article, you will learn how to choose a machine learning algorithm.
• Algorithms Of Microsoft Azure Machine LearningJul 05, 2017. Every Data Science and Machine Learning beginner has only one question in mind: how to start with Machine Learning or how to choose algorithms in Machine Learning, So let's understand Algorithms of Microsoft Azure Machine learning in this article
• Key Based Cryptographic AlgorithmsSep 23, 2016. In this article, you will learn about Key based cryptographic algorithms.
• Using PLINQ to Improve Learning AlgorithmsNov 30, 2009. PLINQ is a welcome addition to the .NET 4.0 framework, allowing us to operate on collection elements in parallel. This article examines the performance improvements of PLINQ over LINQ when doing heavy calculations on a large collection of genomes in a particular learning algorithm.
• Shortest Unique Prefix for Every Word (Trie)Jul 20, 2026. Discover the shortest unique prefix for every word in an array using a Trie. Efficiently identify distinct word beginnings with this optimized algorithm.
• Max Absolute Difference of Two Subarrays (Kadane's Algorithm)Jul 17, 2026. Solve the max absolute difference of two non-overlapping subarrays in O(n) using Kadane's Algorithm and four helper arrays.
• Part 2: Knowledge Representation and Reasoning in AIJul 15, 2026. A practical explanation of classical AI foundations, including search algorithms, knowledge graphs, ontologies, rule-based systems, and why explicit programming falls short.
• Smallest Non-Zero Number | Greedy + Reverse TraversalJul 14, 2026. Find the smallest non-zero starting value for x to keep it non-negative throughout array processing using a greedy reverse traversal.
• Ways to Express a Number as Sum of Consecutive Natural NumbersJul 10, 2026. Discover how to express a number as a sum of consecutive natural numbers efficiently. Learn the O(vn) mathematical approach.
• Count Pairs in an Array Whose Sum Is Divisible by KJul 09, 2026. Master counting pairs divisible by K in Java. Learn the optimized O(n) approach using remainders and frequency arrays.
• Largest Unblocked Submatrix (Greedy + Sorting)Jul 07, 2026. Find the largest unblocked rectangular area in a grid with blocked rows/columns by identifying max gaps between blocked lines.
• Maximum Sum Path in Two Sorted Arrays (Java)Jul 06, 2026. Find the maximum sum path in two sorted arrays with distinct integers, allowing switches at common elements.
• Ways to Increase LCS by One (Dynamic Programming)Jul 03, 2026. Master dynamic programming to efficiently count LCS increases. Learn prefix/suffix DP for O(nm) solutions, avoiding brute-force recomputation.
• Maximum Subarray Sum by Removing At Most One Element (DP)Jul 01, 2026. Master the Maximum Subarray Sum problem with at most one deletion using dynamic programming. Optimize with O(N) time and O(1) space.
• Max Dot Product with 0 Insertions Jun 29, 2026. Maximize dot product by strategically inserting zeros into array b. This DP solution efficiently finds the optimal alignment by considering element choices.
• Count Matching Subsequences Using Dynamic Programming in JavaJun 26, 2026. Learn how to solve the Count Matching Subsequences problem using Dynamic Programming in Java with an O(n × m) approach, explanation, examples, and code.
• N-Digit Numbers with Strictly Increasing DigitsJun 25, 2026. Generate n-digit numbers with strictly increasing digits. Efficiently construct valid sequences using recursion and backtracking.
• Maximum Area Between BarsJun 22, 2026. Master the 'Maximum Area Between Bars' problem using the efficient two-pointer approach. Learn the optimal O(n) solution for finding the largest container.
• Coverage of All Zeros in a Binary Matrix (Java)Jun 18, 2026. Calculate the coverage of zeros in a binary matrix. Sum coverage for each zero by checking for adjacent ones in four directions.
• Maximum Product Cutting of a Rope Using a Greedy Mathematical ApproachJun 17, 2026. Maximize rope cut product! Discover the optimal strategy of cutting into 3s and a Java solution with O(log n) complexity.
• Impact of Quantum Computing on Blockchain Security: Challenges and Future PerspectivesJun 15, 2026. Quantum computing threatens blockchain security. Learn about Shor's & Grover's algorithms, RSA, ECDSA, SHA-256 vulnerabilities, and quantum-resistant solutions.
• Equal Point in BracketsJun 11, 2026. Find the optimal split point in bracket strings where opening brackets left equal closing brackets right. Efficient O(n) solution.
• Binary Searchable Count Count Binary Searchable Elements in an Unsorted ArrayJun 10, 2026. Discover which elements are discoverable via binary search on unsorted arrays. Learn the O(n) algorithm and its O(log n) space complexity.
• Seating Arrangement ProblemJun 09, 2026. Solve the Seating Arrangement Problem: Determine if k people can be seated in empty seats without adjacent occupancy using a greedy approach.
• Stock Span Problem – Monotonic Stack PatternJun 09, 2026. Master the Stock Span Problem with the Monotonic Stack pattern. Efficiently find consecutive days with lower or equal stock prices in O(n) time.
• Find a Peak Element in a 2D MatrixJun 06, 2026. This article explains how to find a peak element in a 2D matrix efficiently. A peak element is defined as an element that is greater than or equal to its four immediate neighbors (top, bottom, left, right). For edge and corner elements, missing neighbors are treated as negative infinity.
• Lexicographically Smallest String After Removing K Characters Using a Monotonic StackJun 05, 2026. Learn how to find the lexicographically smallest string after removing K characters using a monotonic stack in Java. Includes explanation, dry run, and optimized O(n) solution.
• Palindrome Pairs in an Array of Strings – Java Solution with HashMapJun 05, 2026. Learn how to solve the Palindrome Pairs problem using HashMap and palindrome prefix-suffix checking. Includes intuition, dry run, complexity analysis, and optimized Java code.
• Candy Problem in Java – Greedy O(n) Time and O(1) Space SolutionJun 05, 2026. earn how to solve the Candy problem using an optimal greedy algorithm. Includes intuition, dry run, complexity analysis, and Java solution with O(n) time and O(1) space.
• Expression Contains Redundant Bracket or Not – Java Stack Solution ExplainedJun 05, 2026. Learn how to detect redundant brackets in an expression using a stack. Includes intuition, dry run, complexity analysis, and optimized Java O(n) solution.
• Next Element With Greater Frequency – Java O(n) Stack SolutionJun 05, 2026. Learn how to solve the Next Element With Greater Frequency problem using HashMap and Monotonic Stack. Includes intuition, dry run, complexity analysis, and optimized Java solution.
• Count Subset With Target Sum II – Meet in the Middle Java SolutionJun 05, 2026. Learn how to solve Count Subset With Target Sum II using the Meet in the Middle technique. Includes intuition, dry run, complexity analysis, and optimized Java code.
• Remove K Digits Problem – Greedy Stack Approach to Find the Smallest NumberJun 05, 2026. Learn how to solve the “Remove K Digits” problem using a greedy monotonic stack approach. This article explains how to efficiently remove k digits from a number string to form the smallest possible result while maintaining digit order, along with a Java implementation and clear intuition.
• How to Implement Rate Limiting in ASP.NET Core ApplicationsJun 05, 2026. Learn how to implement Rate Limiting in ASP.NET Core applications using built-in middleware. Explore Fixed Window, Sliding Window, and Token Bucket strategies.
• Difference Between LRU Cache and LFU CacheMay 12, 2026. Explore the LRU vs. LFU cache algorithms! Understand their differences in eviction policies, implementation, and suitability for various applications. Optimize your cache performance now!
• Police and Thieves ProblemApr 30, 2026. Maximize thieves caught by policemen within distance 'k' using a greedy two-pointer approach. Optimal O(n) solution ensures the closest valid pairs are matched first.
• Smallest Window Containing ‘0’, ‘1’, and ‘2’Apr 27, 2026. Master the Sliding Window technique! This guide solves the 'Smallest Window Containing 0, 1, and 2' problem with clear explanations, examples, and Java code. Find the shortest substring efficiently!
• Buildings with SunlightApr 27, 2026. Find buildings visible to sunlight using a greedy algorithm! This problem focuses on array traversal, tracking maximums, and handling edge cases like equal heights. A common interview question!
• Opposite Sign Pair ReductionApr 27, 2026. Master the 'Opposite Sign Pair Reduction' problem! Learn how to efficiently reduce an array using a stack-based approach, simulating collisions. Includes Java code & complexity analysis.
• Number of BSTs From ArrayApr 27, 2026. Calculate the number of unique Binary Search Trees (BSTs) possible for each element in an array as the root. Leverages Catalan numbers for efficient computation.
• Rotten Oranges ProblemApr 27, 2026. Solve the Rotten Oranges problem using multi-source BFS! Find the minimum time to rot all fresh oranges in a grid. Learn the BFS approach with Java code and complexity analysis.
• Chocolates Pickup (Two Robots Problem)Apr 27, 2026. Solve the classic 'Chocolates Pickup' problem with 3D Dynamic Programming! Maximize chocolate collection by two robots moving simultaneously. Java solution included.
• Articulation Point (Cut Vertex)Apr 27, 2026. Master Tarjan's Algorithm to find articulation points (cut vertices) in undirected graphs! Learn to identify critical nodes that disconnect a graph. Includes Java code!
• Partitions with Given DifferenceApr 27, 2026. Solve partition problems by transforming them into subset sum problems! This DP approach efficiently counts subsets with a specific difference. Learn the key formula!
• Form the Largest NumberApr 27, 2026. Master the largest number problem! Learn how to use custom comparators and greedy algorithms to arrange integers for maximum value. Perfect for coding interviews!
• Find H-IndexApr 27, 2026. Master the H-Index problem with this guide! Learn the sorting approach to efficiently find the maximum H-index, balancing paper quantity and citations. Includes Java code!
• Stream First Non-Repeating CharacterApr 27, 2026. Solve the streaming first non-repeating character problem using a queue and frequency array. Learn the algorithm, Java code, complexity, and key takeaways for interviews.
• Max Sum Subarray of Size KApr 27, 2026. Master the sliding window technique to find the maximum sum subarray of size K. This guide provides a clear explanation, Java code, and complexity analysis.
• Count Distinct Elements in Every WindowApr 27, 2026. Master the sliding window technique! Learn how to efficiently count distinct elements in every window of an array using a HashMap. Java solution and complexity analysis included.