33 Part I Data-driven Inference of Fault Tree models I.1 Introduction Part I focuses on the data-driven inference of Fault Tree models. The general research question we address here is how to obtain e!cient and compact Fault Tree models from failure datasets in a robust and scalable manner? This part is structured as follows: Section I.2 summarises the nomenclature used in Part I. Section I.3 reviews the related work common to all chapters. Section I.4 presents the formal definitions used in Part I. The chapters contained here are: Chapter 2. Automatic Inference of Fault Tree Models via Multi-Objective Evolutionary Algorithms ................................................41 Chapter 3. Data-Driven Inference of Fault Tree Models Exploiting Symmetry and Modularisation ....................................................61 Chapter 4. Fault Tree inference using Multi-Objective Evolutionary Algorithms and Confusion Matrix-based metrics ...............................75
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