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Contributing to Lab_KTU_Programs

Thank you for your interest in contributing to our repository! To ensure consistency and organization, please follow the steps below when adding your contributions.

How to Contribute

1. Navigate to the Correct Department

  • Open the folder corresponding to the department your contribution belongs to. The available departments are:
    • CSE
    • CSE-CYBER SECURITY
    • ARTIFICIAL INTELLIGENCE
    • ARTIFICIAL INTELLIGENCE AND DATA SCIENCE

2. Select the Appropriate Lab

  • Inside the department folder, navigate to the folder of the lab where your program should be added.

3. Create a New Folder for Your Program

  • Inside the lab folder, create a new folder. Name this folder according to the name of your program. For example, if your program is "Matrix Multiplication," name the folder MatrixMultiplication.

4. Add the Required Files

Inside your program's folder, add the following files:

  1. Program File

    • This file should contain the code for your program. Name it appropriately based on the programming language used, e.g., MatrixMultiplication.py for Python, MatrixMultiplication.java for Java, etc.
  2. Output File

    • This file should contain the output of your program when executed. Name it output.txt. If there are multiple outputs, you can create separate files like output1.txt, output2.txt, etc.
  3. README File

    • This file should describe what the program does, how it works, and any special instructions for running it. Name it README.md.

5. Commit and Push Your Changes

  • After adding the files, commit your changes with a descriptive commit message, e.g., Added Matrix Multiplication program for CSA Lab.
  • Push the changes to the appropriate branch or create a pull request to the main branch.

Example Folder Structure

├── CSE
│ ├── Lab1
│ │ ├── MatrixMultiplication
│ │ │ ├── MatrixMultiplication.py
│ │ │ ├── output.txt
│ │ │ └── README.md
│ ├── Lab2
│ │ ├── ...
├── CSE-CYBER SECURITY
│ ├── Lab1
│ │ ├── ...

Pull Request Guidelines

  • Ensure your code is properly commented and follows the repository’s coding standards.
  • Your pull request should be linked to a relevant issue if applicable.
  • Before submitting, make sure there are no merge conflicts.

Thank you for your contribution!

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