Automating Suggestion of Ethical Implementation Method on Agile Software Project Management

Project Overview

Automating Suggestion of Ethical Implementation Method on Agile Software Project Management is a tool designed to facilitate the integration of ethical practices in agile software project management. The tool provides automated ethical suggestions based on the methodology outlined in the paper "ECCOLA—A Method for Implementing Ethically Aligned AI Systems" by Vakkuri, Ville, et al., published in the Journal of Systems and Software.

Documentation

This repo is the code for thesis : https://lutpub.lut.fi/handle/10024/168082

Key Features

• Automated ethical suggestions tailored for agile software project management.
• Integration with ECCOLA methodology for ethical AI systems.
• User-friendly GUI for easy interaction and usability.
• Locally run application ensuring data privacy and security.

Installation

Prerequisites

• Operating System: Windows 11
• Python 3.8 or higher
• Git

Step-by-Step Installation

1. Clone the Repository

   • Clone this repository to your local machine using:

     git clone [https://github.com/your-username/your-repository-name.git](https://github.com/cinapr/ECCOLA_AutomatedSuggestion_GUI.git)
     cd your-repository-name

2. Install Required Libraries

   • Install the necessary Python libraries by running:

     .\python.exe -m pip install tkinter

Data Preparation

• Ensure the Vakkuri Dataset is placed in the main directory of the cloned repository.
• For each of the tokenizer and interface you need to ensure the model name and csv name is correct (Check directly on the code)

Running the Scripts

1. Install depedencies

   • Install python depedencies:

     pip install tkinter

2. Run the system

   • run the inference script:

     python main.py

Usage

1. Launch the Application

   • After running the application, the GUI will appear.

2. Navigating the GUI

   • Use the main dashboard to input your project details.
   • Click on the 'Get Suggestions' button to receive ethical recommendations.
   • Review the suggestions and integrate them into your project management practices.

Project Structure

├── main.py
├── CONTROLLER
│   ├── eccoladigital_action.py
│   ├── retrieve_jira_action.py
│   ├── suggestion_action.py
│   ├── training_action.py
├── MODEL
│   ├── LoggerMessage.py
│   ├── ECCOLA.py
├── VIEW
│   ├── DownloadECCOLAQuestions.py
│   ├── eccoladigital.py
│   ├── processing.py
│   ├── retrieve_jira.py
│   ├── training.py
├── RESOURCES
│   ├── clean_text.py
│   ├── profile.png

Main Components

1. main.py: Entry point for the application.
2. CONTROLLER: Handles the application's logic and interaction between the model and view.

• eccoladigital_action.py: Manages actions related to ECCOLA digital operations.
• retrieve_jira_action.py: Handles actions to retrieve data from Jira.
• suggestion_action.py: Provides suggestions based on the retrieved data.
• training_action.py: Manages training actions for the model.

3. MODEL: Contains the application's core data and logic.

• LoggerMessage.py: Manages logging messages.
• ECCOLA.py: Core logic for the ECCOLA methodology.

4. VIEW: Manages the application's user interface.

• DownloadECCOLAQuestions.py: Interface for downloading ECCOLA questions.
• eccoladigital.py: Main ECCOLA digital interface.
• processing.py: Interface for processing user stories and suggestions.
• retrieve_jira.py: Interface for retrieving Jira user stories.
• training.py: Interface for training the model.

5. RESOURCES: Contains additional resources such as scripts and images.

• clean_text.py: Text cleaning utilities.
• profile.png: Profile image.

License

1. LLM OpenAI Privacy Policy OpenAI Privacy Policy OpenAI Security and Privacy OpenAI Enterprise Privacy

2. Other Parts Open-source according to GitHub.

3. Data

• User Stories : Data is run locally on the client machine and is owned privately by the users.
• Sample Data : The data included in this repository is not covered by this license. The data belongs to third parties and is used here solely for demonstration purposes. Users of this repository are not permitted to use, copy, modify, or distribute the data without proper authorization from the respective data owners.
• ECCOLA Questions : The questions included in this story is owned by Vakkuri, Ville, et al. | ECCOLA—A method for implementing ethically aligned AI systems | Journal of Systems and Software 182:111067 | 2021