Algorithm Design Techniques

 Designing efficient algorithms involves structured approaches to problem-solving. Here are some commonly used algorithm design paradigms:

1. Divide and Conquer

   • Breaks a problem into smaller subproblems, solves them recursively, and combines their results.

   • Example: Merge Sort, Quick Sort, Binary Search

2. 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

3. 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

4. Backtracking

   • Explores all possibilities recursively and backtracks when an infeasible solution is found.

   • Example: N-Queens Problem, Sudoku Solver, Hamiltonian Cycle

5. Brute Force

   • Tries all possible solutions and picks the best one.

   • Example: String Matching Algorithms like Naïve Pattern Searching