Formalised responsibility modelling for automated socio-technical systems analysis

Simpson, Robbie (2017) Formalised responsibility modelling for automated socio-technical systems analysis. PhD thesis, University of Glasgow.

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Printed Thesis Information: https://eleanor.lib.gla.ac.uk/record=b3288239

Abstract

Modelling the structure of social-technical systems as a basis for informing
software system design is a difficult compromise. Formal methods struggle to
capture the scale and complexity of the heterogeneous organisations that use
technical systems. Conversely, informal approaches lack the rigour needed to
inform the software design and construction process or enable automated
analysis.

We revisit the concept of responsibility modelling, which models social
technical systems as a collection of actors who discharge their
responsibilities, whilst using and producing resources in the
process. In this thesis responsibility modelling is formalised as a structured approach for
socio-technical system specification and modelling, with
well-defined semantics and support for automated structure and validity
analysis.

We provide structured definitions for entity types and relations, and
define the semantics of delegation and dependency. A constraint logic is
introduced, providing simple specification of complex
interactions between entities. Additionally, we introduce the ability to
explicitly model uncertainty.
To support this formalism, we present a new software toolkit that supports
modelling and automatic analysis of responsibility models in both
graphical and textual form.

The new methodology is validated by applying it to case studies across
different problem domains. A study of nuclear power station emergency planning
is validated by comparison to a similar study performed with earlier forms of
responsibility modelling, and a study of the TCAS mid-air collision avoidance
system is validated by evaluation with domain experts. Additionally, we perform
an explorative study of responsibility modelling understanding and applicability
through a qualitative study of modellers.

Item Type: Thesis (PhD)
Qualification Level: Doctoral
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Colleges/Schools: College of Science and Engineering > School of Computing Science
Supervisor's Name: Storer, Dr. Tim
Date of Award: 2017
Depositing User: Dr Robbie Simpson
Unique ID: glathesis:2017-8495
Copyright: Copyright of this thesis is held by the author.
Date Deposited: 11 Oct 2017 16:00
Last Modified: 15 Nov 2017 14:25
URI: http://theses.gla.ac.uk/id/eprint/8495

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