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Making Simulink Models Robust with Respect to Change

dc.contributor.advisorWassyng, Alan
dc.contributor.advisorLawford, Mark
dc.contributor.authorJaskolka, Monika
dc.contributor.departmentComputing and Softwareen_US
dc.date.accessioned2021-01-02T22:43:56Z
dc.date.available2021-01-02T22:43:56Z
dc.date.issued2020
dc.descriptionPhD Thesis (Software Engineering)en_US
dc.description.abstractModel-Based Development (MBD) is an approach that uses software models to describe the behaviour of embedded software and cyber-physical systems. MBD has become an increasingly prevalent paradigm, with Simulink by MathWorks being the most widely used MBD platform for control software. Unlike textual programming languages, visual languages for MBD such as Simulink use block diagrams as their syntax. Thus, some software engineering principles created for textual languages are not easily adapted to this graphical notation or have not yet been supported. A software engineering principle that is not readily supported in Simulink is the modularization of systems using information hiding. As with all software artifacts, Simulink models must be constantly maintained and are subject to evolution over their lifetime. This principle hides likely changes, thus enabling the design to be robust with respect to future changes. In this thesis, we perform repository mining on an industry change management system of Simulink models to understand how they are likely to change. Then, we explore the various modelling mechanisms available in the Simulink language to see how they could support modular design with information hiding. Next, we propose a module structure, syntactic interface, and modelling conventions for Simulink designs, which are supported by our open-source Simulink Module Tool. Finally, we apply the proposed techniques on case studies from the aerospace and nuclear domains, in order to demonstrate their practicality and validate their effectiveness. Overall, the approach helped support information hiding by encapsulating secrets and facilitating likely changes. It also had a positive effect on interface complexity, cohesion, and coupling. The larger system also exhibited reductions to cyclomatic complexity, testing effort, and execution time, but the smaller case study benefited less in these areas.en_US
dc.description.degreeDoctor of Philosophy (PhD)en_US
dc.description.degreetypeThesisen_US
dc.identifier.urihttp://hdl.handle.net/11375/26126
dc.language.isoenen_US
dc.subjectSimulinken_US
dc.subjectModularityen_US
dc.subjectModel-Based Developmenten_US
dc.titleMaking Simulink Models Robust with Respect to Changeen_US
dc.typeThesisen_US

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