{"id":22984866,"url":"https://github.com/webdevbysubha/daa-lab","last_synced_at":"2025-04-02T10:45:27.457Z","repository":{"id":256019855,"uuid":"854135692","full_name":"webdevbysubha/DAA-LAB","owner":"webdevbysubha","description":null,"archived":false,"fork":false,"pushed_at":"2024-09-08T13:38:32.000Z","size":11,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-02-08T01:52:36.628Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"C","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/webdevbysubha.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-09-08T13:28:57.000Z","updated_at":"2024-09-08T13:38:35.000Z","dependencies_parsed_at":"2024-09-08T15:08:17.766Z","dependency_job_id":"5962f0fb-f7bc-451a-9901-93632f9ef8fd","html_url":"https://github.com/webdevbysubha/DAA-LAB","commit_stats":null,"previous_names":["webdevbysubha/daa-lab"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/webdevbysubha%2FDAA-LAB","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/webdevbysubha%2FDAA-LAB/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/webdevbysubha%2FDAA-LAB/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/webdevbysubha%2FDAA-LAB/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/webdevbysubha","download_url":"https://codeload.github.com/webdevbysubha/DAA-LAB/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":246802612,"owners_count":20836369,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-12-15T03:18:13.279Z","updated_at":"2025-04-02T10:45:27.404Z","avatar_url":"https://github.com/webdevbysubha.png","language":"C","funding_links":[],"categories":[],"sub_categories":[],"readme":"# DAA LAB\n\nThis repository contains implementations and explanations for various **Design and Analysis of Algorithms (DAA)** topics covered in the lab. Below is the list of algorithms and problems included:\n\n---\n\n## Table of Contents\n1. [Quick Sort](#quick-sort)\n2. [Merge Sort](#merge-sort)\n3. [Matrix Chain Multiplication](#matrix-chain-multiplication)\n4. [Travelling Salesperson Problem](#travelling-salesperson-problem)\n5. [Bellman-Ford Shortest Path](#bellman-ford-shortest-path)\n6. [Fractional Knapsack](#fractional-knapsack)\n7. [Job Sequence Problem](#job-sequence-problem)\n8. [N-Queen Problem](#n-queen-problem)\n9. [Graph Coloring](#graph-coloring)\n10. [Kruskal's Algorithm](#kruskals-algorithm)\n11. [Prim's Algorithm](#prims-algorithm)\n12. [Breadth-First Search (BFS) and Depth-First Search (DFS)](#bfs-and-dfs)\n\n---\n\n## 1. Quick Sort\nQuick Sort is a highly efficient sorting algorithm that uses a divide-and-conquer approach to sort elements.\n\n- **Time Complexity**: O(n log n) on average\n- **Space Complexity**: O(log n)\n\n[Learn More](https://en.wikipedia.org/wiki/Quicksort)\n\n---\n\n## 2. Merge Sort\nMerge Sort is a stable, comparison-based sorting technique using a divide-and-conquer approach.\n\n- **Time Complexity**: O(n log n)\n- **Space Complexity**: O(n)\n\n[Learn More](https://en.wikipedia.org/wiki/Merge_sort)\n\n---\n\n## 3. Matrix Chain Multiplication\nMatrix Chain Multiplication is a dynamic programming algorithm used to find the most efficient way to multiply matrices.\n\n- **Time Complexity**: O(n^3)\n- **Space Complexity**: O(n^2)\n\n[Learn More](https://en.wikipedia.org/wiki/Matrix_chain_multiplication)\n\n---\n\n## 4. Travelling Salesperson Problem (TSP)\nTSP is a classic optimization problem where the goal is to find the shortest possible route that visits each city exactly once and returns to the origin city.\n\n- **Time Complexity**: O(n^2 * 2^n) using dynamic programming\n- **Space Complexity**: O(n * 2^n)\n\n[Learn More](https://en.wikipedia.org/wiki/Travelling_salesman_problem)\n\n---\n\n## 5. Bellman-Ford Shortest Path\nBellman-Ford is an algorithm used to compute the shortest paths from a single source vertex to all other vertices in a weighted graph, even with negative weight edges.\n\n- **Time Complexity**: O(VE)\n- **Space Complexity**: O(V)\n\n[Learn More](https://en.wikipedia.org/wiki/Bellman%E2%80%93Ford_algorithm)\n\n---\n\n## 6. Fractional Knapsack\nThe Fractional Knapsack problem is an optimization problem where fractions of items can be taken to maximize the total value.\n\n- **Time Complexity**: O(n log n)\n- **Space Complexity**: O(1)\n\n[Learn More](https://en.wikipedia.org/wiki/Knapsack_problem#Fractional_knapsack_problem)\n\n---\n\n## 7. Job Sequence Problem\nThis problem is solved using a greedy algorithm to maximize profit by scheduling jobs within their deadlines.\n\n- **Time Complexity**: O(n log n)\n- **Space Complexity**: O(n)\n\n[Learn More](https://en.wikipedia.org/wiki/Job_scheduling_problem)\n\n---\n\n## 8. N-Queen Problem\nThe N-Queen problem is a classic backtracking algorithm where the goal is to place N queens on an N×N chessboard such that no two queens threaten each other.\n\n- **Time Complexity**: O(N!)\n- **Space Complexity**: O(N)\n\n[Learn More](https://en.wikipedia.org/wiki/Eight_queens_puzzle)\n\n---\n\n## 9. Graph Coloring\nGraph Coloring is the problem of assigning colors to the vertices of a graph so that no two adjacent vertices share the same color.\n\n- **Time Complexity**: O(V+E)\n- **Space Complexity**: O(V)\n\n[Learn More](https://en.wikipedia.org/wiki/Graph_coloring)\n\n---\n\n## 10. Kruskal's Algorithm\nKruskal’s algorithm is a greedy algorithm used to find a minimum spanning tree for a connected weighted graph.\n\n- **Time Complexity**: O(E log E)\n- **Space Complexity**: O(V)\n\n[Learn More](https://en.wikipedia.org/wiki/Kruskal%27s_algorithm)\n\n---\n\n## 11. Prim's Algorithm\nPrim’s algorithm is another greedy algorithm used to find the minimum spanning tree of a graph.\n\n- **Time Complexity**: O(E log V)\n- **Space Complexity**: O(V)\n\n[Learn More](https://en.wikipedia.org/wiki/Prim%27s_algorithm)\n\n---\n\n## 12. Breadth-First Search (BFS) and Depth-First Search (DFS)\nBFS and DFS are fundamental graph traversal algorithms used in various applications.\n\n- **BFS Time Complexity**: O(V + E)\n- **DFS Time Complexity**: O(V + E)\n- **Space Complexity**: O(V)\n\n[Learn More](https://en.wikipedia.org/wiki/Breadth-first_search) | [DFS](https://en.wikipedia.org/wiki/Depth-first_search)\n\n---\n\n## Contributions\nFeel free to fork the repository and contribute by submitting pull requests.\n\n---\n\n## License\nThis project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.\n\n---\n\n---\n\n## 👤 Author\n\n~ **Subha Mondal**\n\n(Feel free to reach out if you have any questions or suggestions!)\n\n---\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fwebdevbysubha%2Fdaa-lab","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fwebdevbysubha%2Fdaa-lab","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fwebdevbysubha%2Fdaa-lab/lists"}