https://github.com/jain131102/neocolab

CSE3004_Design and Analysis of Algorithms Lab_ NEOCOLAB
https://github.com/jain131102/neocolab

daa java neocolab vit

Last synced: 2 months ago
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CSE3004_Design and Analysis of Algorithms Lab_ NEOCOLAB

• Host: GitHub
• URL: https://github.com/jain131102/neocolab
• Owner: Jain131102
• Created: 2025-04-13T17:12:30.000Z (6 months ago)
• Default Branch: main
• Last Pushed: 2025-04-20T20:12:46.000Z (6 months ago)
• Last Synced: 2025-05-31T01:09:45.033Z (5 months ago)
• Topics: daa, java, neocolab, vit
• Language: Java
• Homepage: https://vitapcolab129.examly.io/
• Size: 410 KB
• Stars: 12
• Watchers: 1
• Forks: 3
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# Design and Analysis of Algorithms Lab

Welcome to the **Design and Analysis of Algorithms Lab-NeoColab** repository! This collection contains structured lab work for learning and implementing core algorithmic concepts using Java.

## 📁 Repository Contents

Each lab focuses on a different topic related to algorithms and data structures:

| Sr. No. | Title                                | Description                                               |

|--------:|--------------------------------------|-----------------------------------------------------------|

| Lab 0 |Base Codes                          | Contains the core logic implementations.            |

| Lab 1   | Prim's and Kruskal's                 | Implementation of Minimum Spanning Tree algorithms.       |

| Lab 2   | Strongly Connected Graph             | Algorithms like Kosaraju's or Tarjan's for SCC detection. |

| Lab 3   | Greedy & Dynamic Programming         | Greedy and DP-based problem solving techniques.           |

| Lab 4   | Optimal Ordering                     | Solutions to sequencing and scheduling problems.          |

| Lab 5   | Shortest Path Algorithm              | Dijkstra's and/or Bellman-Ford implementations.           |

| Lab 6   | Binary Search Tree                   | Implementation and traversal of BSTs.                     |

| Lab 7   | 0/1 Knapsack                         | Solving the classic 0/1 Knapsack problem using backtracking.|

| PDF        | Concept Builder 1-7                  | A compiled reference document with multiple-choice question (MCQ) to build conceptual understanding for Labs 1 to 7.|

| Excel Sheet        | Concept Builder - Practice                  | 200 multiple-choice question (MCQ) to practice more .|

##  🤝 Contributors

- ![GitHub](https://img.shields.io/badge/GitHub-JoyForCode-blue?style=flat-square) [JoyForCode](https://github.com/JoyForCode)

- ![GitHub](https://img.shields.io/badge/GitHub-Jain131102-blue?style=flat-square) [Jain131102](https://github.com/Jain131102)

## 📜 License

This project is open-source and available under the ![MIT License](https://img.shields.io/badge/license-MIT-green?style=flat-square) [MIT License](https://opensource.org/licenses/MIT).

Feel free to contribute by improving documentation, optimizing code, or adding new exercises!