Application of Business Process Modelling Methodology for Enhancing the Software Validation Processes

Nayeem Al-Tamzid Bhuiyan

Master's thesis

Abstract:

This thesis presents an innovative approach to applying Business Process Modeling (BPM) methodologies in software validation by integrating Generative Artificial Intelligence (AI) for automatic test case generation, with potential extensions to internal portal automation. The current landscape of software validation practices is critically analyzed, highlighting ongoing skepticism, frequent downtimes, and the associated long-term costs. BPMN (Business Process Model and Notation) is introduced as an effective tool for re-engineering these processes. The report delves into how Generative AI can revolutionize key validation activities while also addressing its limitations, challenges, and ethical considerations. By combining BPM with Generative AI, the validation process becomes more efficient, transparent, and intelligent. This study establishes a synergistic framework for software validation that not only enhances effectiveness.

Keywords

Generative AI, Software Validation, Automation, Partner Applications, AI-Driven Testing, Validation Framework, Test-Case Generation, Software Quality Assurance

Jazyk práce: English

Datum vytvoření / odevzdání či podání práce: 2. 12. 2025

Obhajoba závěrečné práce

• Obhajoba proběhla 3. 2. 2026
• Vedúci: doc. Ing. Milan Houška, Ph.D.
• Oponent: Martin Horák, externi

Czech University of Life Sciences Prague

Faculty of Economics and Management

Master programme:
Informatics