Design and Analysis of Algorithms (DAA)

This repository contains C++ implementations of core algorithmic paradigms studied in the Design and Analysis of Algorithms (DAA) course. These paradigms focus on designing efficient solutions and analyzing their time and space complexity.

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Algorithms Covered

1. Dynamic Programming

• Used for problems with overlapping subproblems and optimal substructure
• Improves efficiency by storing intermediate results
• Example: Fibonacci sequence

2. Backtracking

• Systematically explores all possible solutions
• Backtracks when a partial solution is not valid
• Example: Binary string generation

3. Divide and Conquer

• Divides a problem into smaller subproblems
• Solves recursively and combines results
• Example: Merge Sort

4. Greedy Algorithms

• Makes the locally optimal choice at each step
• Produces optimal solutions for certain problems
• Example: Coin Change

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Language Used

• C++

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Applications

• DAA coursework and lab assignments
• Algorithm design and complexity analysis
• Technical interview preparation

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