MATISSE Tool: Intelligent Test Scenario and Test Case Generation Platform

MATISSE Tool is a modern test automation platform designed to optimize software testing processes while offering a user-friendly experience. It has been developed with advanced technologies to generate test scenarios and detailed test cases from various documents.

Installation Guide

This document provides detailed instructions on how to install and set up the Smart Test Generation Tool.

Step 1: Clone the Repository

First, clone the repository to your local machine:

git clone <repository_url>
cd <repository_name>

Step 2: Set Up a Virtual Environment (Optional but Recommended)

Create and activate a virtual environment to isolate the dependencies:

For Windows:

python -m venv venv
venv\Scripts\activate

For macOS/Linux:

python3 -m venv venv
source venv/bin/activate

Step 3: Install Dependencies

Use the following command to install all the necessary Python libraries listed in the requirements.txt file:

pip install -r requirements.txt

Key Libraries Installed

• Streamlit: A framework for building interactive web applications in Python.
• Pydantic: A library for data validation and parsing using Python type annotations.
• Llama Index: Provides integrations for managing and querying large language models.
• Requests: Enables making HTTP requests to interact with APIs.
• JSON: Used for handling JSON data processing.
• UUID: Generates universally unique identifiers.
• Datetime: Handles timestamping for logs and operations.

Step 4: Run the Application

Once everything is set up, you can run the application using the following command:

streamlit run app.py

This will launch the Smart Test Generation Tool in your default web browser.

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You're now ready to use the Smart Test Generation Tool!

Features

• Functional and Non-Functional Tests: Identifies appropriate test categories based on document content and creates contextually accurate test scenarios.
• Test Case Generation: Derives specific and detailed test cases from test scenarios.
• User-Friendly Interface: Provides an intuitive Streamlit-based interface for easy document upload, test category selection, and scenario customization.
• LLM Integration: Utilizes modern large language models such as Llama, Mistral, and Codellama to generate test scenarios.
• Flexible Data Management: Manages session data, user inputs, and test results using MongoDB.

Technologies Used

• LLM (Large Language Model): Generates context-aware test scenarios using natural language processing technologies.
• Ollama: A platform that simplifies the integration and execution of LLM models.
• Streamlit: Offers a user interface and real-time processing support.
• MongoDB: Provides flexible and scalable data management.