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 To evaluate the efficiency of an algorithm, we analyze its performance using the following measures: 1. Time Complexity Represents the time taken by an algorithm to run as a function of input size (n). Expressed using Big-O notation (O). Examples: O(1) - Constant time O(log n) - Logarithmic time (Binary Search) O(n) - Linear time (Linear Search) O(n log n) - Log-linear time (Merge Sort) O(n²) - Quadratic time (Bubble Sort) 2. Space Complexity Represents the memory required by an algorithm. Important for optimizing performance in memory-constrained environments. 3. Best, Average, and Worst Case Analysis Best Case : Minimum time required (ideal scenario) Average Case : Expected performance over different inputs Worst Case : Maximum time required (upper bound)

 Designing efficient algorithms involves structured approaches to problem-solving. Here are some commonly used algorithm design paradigms: Divide and Conquer Breaks a problem into smaller subproblems, solves them recursively, and combines their results. Example: Merge Sort, Quick Sort, Binary Search Dynamic Programming Solves problems by breaking them into overlapping subproblems and storing results to avoid redundant computations. Example: Fibonacci Series, Knapsack Problem, Longest Common Subsequence Greedy Algorithms Makes locally optimal choices at each step with the hope of finding the global optimum. Example: Huffman Coding, Kruskal’s Algorithm, Prim’s Algorithm Backtracking Explores all possibilities recursively and backtracks when an infeasible solution is found. Example: N-Queens Problem, Sudoku Solver, Hamiltonian Cycle Brute Force Tries all possible solutions and picks the best one. Example: String Matching Algorithms like Naïve Pattern Searching

  Introduction HTML ( HyperText Markup Language ) is the backbone of web development. It provides the structure for web pages and allows developers to organize and display content effectively. Whether you’re a beginner stepping into the world of coding or someone looking to refresh their knowledge, understanding HTML is the first step towards creating stunning websites. In this guide, we’ll cover: ✅ What HTML is ✅ Basic structure of an HTML document ✅ Essential HTML tags ✅ Formatting and styling text ✅ Adding images, links, and lists ✅ Forms and tables By the end, you’ll be able to write and understand basic HTML code! 1. What is HTML? HTML is a markup language that structures content on the web. Unlike programming languages like JavaScript or Python, HTML doesn’t have logic or calculations—it simply defines the arrangement of elements like headings, paragraphs, images, and links on a webpage. 👉 HTML files have the extension .html and are read by web browsers to display content ...

 An algorithm is a finite set of instructions designed to perform a specific task. It takes input, processes it through a sequence of well-defined steps, and produces output. The efficiency of an algorithm is measured in terms of time complexity and space complexity.

 The Design and Analysis of Algorithms is a fundamental topic in computer science, essential for solving complex computational problems efficiently. Algorithms form the backbone of software development, enabling optimal problem-solving strategies. This blog delves into the core principles of algorithm design, analysis techniques, and real-world applications.