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Semantic Differencing of Domain-Specific Models

   Department of Computer Science

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  Dr D Kolovos  No more applications being accepted  Funded PhD Project (Students Worldwide)

About the Project

Model-based systems engineering (MBSE) is the practice of raising domain-specific models to first-class artefacts of the software and systems engineering process, using such models to analyse, simulate and reason about properties of the system under development, and eventually often auto-generate a part of its implementation. MBSE is used extensively in organisations such as Rolls-Royce that produce business- or safety-critical software, where defects can have catastrophic effects (e.g. loss of life) or can be very expensive to remedy (e.g. require large scale product recalls).

At the heart of MBSE processes are domain-specific models, expressed in bespoke modelling languages, that describe problems and solutions at an appropriate level of abstraction. As domain-specific models evolve over time, understanding how they change in each iteration is important for quality and impact management purposes. 

This project will investigate approaches for differencing domain-specific models and presenting the identified changes using effective semantics-aware visualisations in close collaboration with Rolls-Royce. For more context about our background with Rolls-Royce in the field of MBSE, please read this open-access article on a domain-specific modelling workbench (CaMCOA Studio) we have been collaborating on over the last few years, which won the Best Paper award in the Practice and Innovation Track of the 21st ACM/IEEE International Conference on Model-Driven Engineering Languages and Systems.

The key research questions to be addressed by this project are the following:

- To what extent can the graphical syntax of a domain-specific language be reused to visualise differences in models that conform to it in a meaningful way?

- Can bespoke transformations produce more effective semantics-aware visualisations than generic abstract-syntax driven differencing algorithms (e.g. such as those implemented in tools like EMFCompare and EMF Diff/Merge)?

- If so, can commonalities be identified in such bespoke transformations, which could be pulled up to a higher level of abstraction and simplify their development?

You will be part of the Automated Software Engineering (ASE) group of the Department of Computer Science, where we develop novel methods and tools for automated model-driven analysis, design, development, deployment, and management of complex software-intensive systems. We are global leaders in model-driven software engineering research and we engage actively with industry in the UK and world-wide through open-source software communities, collaborative research and development projects and knowledge transfer partnerships.

Our research strives to automate solutions to repetitive and error-prone problems in software engineering. By doing so we support software engineers in focusing on those challenges that require their insight, design expertise, and competencies. Our research particularly benefits engineers and architects of large-scale enterprise software systems, and of complex software-intensive systems in high-integrity industries such as aerospace, robotics and automotive. We collaborate closely with industrial partners such as Rolls-Royce, Leonardo, Capgemini, and British Telecom, and open-source tools and frameworks we develop are used to apply and teach automated model-driven software engineering in many organisations and universities worldwide.

You will also be part of the Doctoral Centre for Safe, Ethical and Secure Computing at the University of York. Training activities they will be involved in will include interdisciplinary sandpits and mentored teaching, as well as workshops on ethics, scientific storytelling and policymaking. In addition to weekly supervision meetings, the Centre’s students will also have end-of-the-week cohort meetings to reflect on the activities of the past and coming week, and to share good practices in research productivity, resilience and overall well-being.

We welcome applications from home and international students. Applications for this scholarship should be submitted through the University of York's online system (please mention the title of the project in your application and indicate Prof. Dimitris Kolovos as the supervisor).

Funding Notes

This studentship is fully funded for 3.5 years by an Engineering and Physical Sciences Research Council (EPSRC) Doctoral Training Partnership studentship and covers: (i) a tax-free annual stipend at the standard Research Council rate (£16,062 pa for 2022 entry), (ii) tuition fees (iii) research training and consumables
Not all projects will be funded; candidates will be appointed via a competitive process.

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