Model-Driven Engineering (MDE) promises to enhance system development by reducing development time, and increasing productivity and quality. MDE is gaining popularity in several industry sectors, and is attractive also for critical systems where they can reduce efforts and costs for verification and validation (V&V), and can ease certification. This thesis proposes a novel model-driven life cycle that is tailored to the development of critical railway systems. It also integrates an original approach for model-driven system validation, based on a new model named Computation Independent Test model (CIT). Moreover, the process supports the Failure Modes and Effect Analysis (FMEA), with a novel approach to conduct Model-Driven FMEA, based on custom SysML Diagram, namely the FMEA Diagram, and Prolog. The approaches have been experimented in multiple real-world case studies, from railway and automative domains.

A Model-Driven Methodology for Critical Systems Engineering

2016

Abstract

Model-Driven Engineering (MDE) promises to enhance system development by reducing development time, and increasing productivity and quality. MDE is gaining popularity in several industry sectors, and is attractive also for critical systems where they can reduce efforts and costs for verification and validation (V&V), and can ease certification. This thesis proposes a novel model-driven life cycle that is tailored to the development of critical railway systems. It also integrates an original approach for model-driven system validation, based on a new model named Computation Independent Test model (CIT). Moreover, the process supports the Failure Modes and Effect Analysis (FMEA), with a novel approach to conduct Model-Driven FMEA, based on custom SysML Diagram, namely the FMEA Diagram, and Prolog. The approaches have been experimented in multiple real-world case studies, from railway and automative domains.
2016
it
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14242/333576
Il codice NBN di questa tesi è URN:NBN:IT:BNCF-333576