| KEYWORD |
DAUIN - GR-16 - SOFTWARE ENGINEERING GROUP - SOFTENG
Enhancing Software Testing Through Generative AI: A Revolutionary approach in the automotive context
Thesis in external company
keywords AI, AUTOMOTIVE, TESTING
Reference persons RICCARDO COPPOLA
Research Groups DAUIN - GR-16 - SOFTWARE ENGINEERING GROUP - SOFTENG
Thesis type COMPANY STAGE
Description 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 Intelligence (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. Harnessing the power 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.
Required skills Strong knowledge of python (demonstrated experience with pygame framework is a plus)
Demonstrated interest in the Autonomous Driving
Demonstrated interest in computer vision techniques
Notes Skills acquired:
Sensor modelling, virtualization and setup
Synthetic data generation and ground truth validation
Carla Simulator for autonomous driving function development and validation
Deadline 26/02/2025
PROPONI LA TUA CANDIDATURA