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  KEYWORD

Enhancing Software Testing Through Generative AI

keywords AI, AUTOMOTIVE, TESTING

Reference persons RICCARDO COPPOLA

Research Groups DAUIN - GR-16 - SOFTWARE ENGINEERING GROUP - SOFTENG

Thesis type INDUSTRY

Description Thesis work at Concept Quality Reply

Context:
In the specific domain of vehicle diagnostics and IoT, achieving thorough End-to-End (E2E) validation is critical for ensuring the reliability and
performance of integrated systems. This necessitates innovative approaches to software testing, and Generative Artificial Int elligence (Generative AI)
emerges as a promising tool to streamline and augment testing processes.

Description:
This thesis delves into the integration and application of Generative AI in the field of software testing. y harnessing the p ower of Generative AI, this
research aims to enhance the efficiency, accuracy, and comprehensiveness of testing activities, especially within the context of IoT and connected
vehicles.

Objectives:
• Explore the potential of Generative AI in generating comprehensive and diverse test cases for intricate software systems.
• Investigate how Generative AI can expedite the creation of test scenarios and data, mimicking real-world usage and improving test coverage.
• Assess the impact of Generative AI on the overall efficiency and effectiveness of End-to-End (E2E) validation processes, particularly in IoT and
connected vehicle systems.
• Develop methodologies to integrate Generative AI seamlessly into the software testing life cycle, with a focus on optimizing resource utilization and
reducing testing time.

• Pre-requisites:
• Proficiency in software development and testing methodologies.
• Familiarity with Generative AI concepts and principles.
• Understanding of IoT and connected vehicle technologies.

• Skills acquired:
• Java, Postman, Selenium, CANalyzer, CAPL, Generative AI frameworks (e.g., GPT-3, GPT-4), Python, Machine Learning libraries (e.g.,
TensorFlow, PyTorch), IoT frameworks and protocols, Connected vehicle technologies, Automated testing tools.


Deadline 03/09/2025      PROPONI LA TUA CANDIDATURA