| KEYWORD |
Use of AI for automated test script generation
Reference persons RICCARDO COPPOLA
Research Groups DAUIN - GR-16 - SOFTWARE ENGINEERING GROUP - SOFTENG
Thesis type INDUSTRY
Description Thesis work at Concept Quality Reply
Context:
This thesis recognizes the pivotal role of test case generation, using generative AI, to ensure product quality and reliability throughout the entire product lifecycle, ultimately
enhancing user satisfaction and reducing cost.
Description:
Here's a brief description of the activities the candidate for the thesis might undertake within the team under the guidance of an expert tutor:
• Review relevant research on generative AI and automated testing.
• Define the scope and challenges of AI-based test case generation.
• Gather datasets for model training and evaluation.
• Create AI models for test case generation.
• Design experiments to assess model performance.
• Analyze experiment results to measure system effectiveness.
• Refine the AI model based on evaluation feedback.
• Familiarity with various test frameworks for different aspects of mobile app testing (e.g., UI testing, integration testing).
• Hands-on experience with popular testing frameworks (e.g., Selenium, Appium).
• Write and present the research findings in a thesis.
Objectives:
Use generative AI to transform natural language requirements from different formats (PDF, PPT, Word) into a complete set of test cases, and to generate the final automated script
(Appium, Selenium) of the corresponding automated tests.
Pre-requisites:
• Knowledge of Java, python, javascript, html, css
• Knowledge of automated testing (e.g., Selenium, Appium).
• Knowledge of AI and Machine learning approaches
• Demonstrated interest in automated testing, Generative AI algorithms
Skills acquired:
• Learning about Generative AI to speed-up testing and validation processes
• Learning about automated generative process from functional requirements to test
cases for financial services
Deadline 03/09/2025
PROPONI LA TUA CANDIDATURA