This thesis examines the evolution of software testing in the era of Artificial Intelligence (AI), with particular focus on the transition from traditional engineering practices to intelligent, adaptive, and automated methodologies. The first part provides a technical and historical overview of software testing within the broader field of software engineering, outlining foundational principles, manual strategies, and pre-AI automation techniques. The second part explores how AI is transforming testing through machine learning, intelligent test generation, and systems capable of addressing complexity, uncertainty, and user-centric requirements. The third part focuses on the application of AI to user interface (UI) and user experience (UX) testing, highlighting how emerging design paradigms challenge conventional testing methods. Finally, the fourth part presents an original case study on the use of AI-based testing for a fluid and modern interface inspired by Apple’s “Liquid Glass” paradigm introduced in iOS 26. The thesis offers a critical and structured analysis of ongoing transformations and future perspectives in intelligent software testing.
Questa tesi analizza l’evoluzione del software testing nell’era dell’Intelligenza Artificiale (IA), con particolare attenzione alla transizione dalle pratiche ingegneristiche tradizionali verso approcci intelligenti, adattivi e automatizzati. La prima parte offre una panoramica tecnica e storica del testing del software nel contesto dell’ingegneria del software, illustrando principi fondamentali, strategie manuali e automazione pre-IA. La seconda parte approfondisce come l’IA stia trasformando il testing attraverso tecniche come il machine learning, la generazione automatica dei test e l’impiego di sistemi capaci di gestire complessità, incertezza e centralità dell’utente. La terza parte si concentra sull’applicazione dell’AI al testing dell’interfaccia utente (UI) e dell’esperienza utente (UX), mettendo in luce come le nuove esigenze progettuali sfidino i metodi tradizionali. Infine, la quarta parte presenta un caso studio originale sull’utilizzo dell’IA per il testing di un’interfaccia fluida e contemporanea, ispirata al paradigma “Liquid Glass” introdotto da Apple in iOS 26. Il lavoro propone una riflessione critica sulle trasformazioni in atto e sulle prospettive future del testing software intelligente.
L’EVOLUZIONE DEL SOFTWARE TESTING NELL’ERA DELL’INTELLIGENZA ARTIFICIALE
NOCE, GIANMARCO
2024/2025
Abstract
This thesis examines the evolution of software testing in the era of Artificial Intelligence (AI), with particular focus on the transition from traditional engineering practices to intelligent, adaptive, and automated methodologies. The first part provides a technical and historical overview of software testing within the broader field of software engineering, outlining foundational principles, manual strategies, and pre-AI automation techniques. The second part explores how AI is transforming testing through machine learning, intelligent test generation, and systems capable of addressing complexity, uncertainty, and user-centric requirements. The third part focuses on the application of AI to user interface (UI) and user experience (UX) testing, highlighting how emerging design paradigms challenge conventional testing methods. Finally, the fourth part presents an original case study on the use of AI-based testing for a fluid and modern interface inspired by Apple’s “Liquid Glass” paradigm introduced in iOS 26. The thesis offers a critical and structured analysis of ongoing transformations and future perspectives in intelligent software testing.I documenti in UNITESI sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
https://hdl.handle.net/20.500.14253/69852