Constructing runtime models with bigraphs to address ubiquitous computing service composition volatility

In this thesis, we explore the appropriateness of the language abstractions provided by Bigraphs to construct a model at runtime to tackle the problem of volatility in a service composition running on a mobile device. Our contributions to knowledge are as follows: 1) We have shown that Bigraphs (Milner, 2009) are suitable for expressing models at runtime. 2) We have offered Bigraph language abstractions as an appropriate solution to some of the research problems posed by the models at runtime community (Aßmann et al., 2012). 3) We have discussed the general lessons learnt from using Bigraphs for a practical application such as a model at runtime. 4) We have discussed the general lessons learnt from our experiences of designing models at runtime. 5) We have implemented the model at runtime using the BPL Tool (ITU, 2011) and have experimentally studied the response times of our Bigraphical model. We have suggested appropriate enhancements for the tool based on our experiences. We present techniques to parameterize the reaction rules so that the matching algorithm of the BPL Tool returns a single match giving us the ability to dynamically program the model at runtime. We also show how to query the Bigraph structure

Toward Accessible Multilevel Modeling in Systems Biology: A Rule-based Language Concept

Promoted by advanced experimental techniques for obtaining high-quality data and the steadily accumulating knowledge about the complexity of life, modeling biological systems at multiple interrelated levels of organization attracts more and more attention recently. Current approaches for modeling multilevel systems typically lack an accessible formal modeling language or have major limitations with respect to expressiveness. The aim of this thesis is to provide a comprehensive discussion on associated problems and needs and to propose a concrete solution addressing them

Applications of matching theory in constraint programming

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Continuous-time temporal logic specification and verification for nonlinear biological systems in uncertain contexts

In this thesis we introduce a complete framework for modelling and verification of biological systems in uncertain contexts based on the bond-calculus process algebra and the LBUC spatio-temporal logic. The bond-calculus is a biological process algebra which captures complex patterns of interaction based on affinity patterns, a novel communication mechanism using pattern matching to express multiway interaction affinities and general kinetic laws, whilst retaining an agent-centric modelling style for biomolecular species. The bond-calculus is equipped with a novel continuous semantics which maps models to systems of Ordinary Differential Equations (ODEs) in a compositional way. We then extend the bond-calculus to handle uncertain models, featuring interval uncertainties in their species concentrations and reaction rate parameters. Our semantics is also extended to handle uncertainty in every aspect of a model, producing non-deterministic continuous systems whose behaviour depends either on time-independent uncertain parameters and initial conditions, corresponding to our partial knowledge of the system at hand, or time-varying uncertain inputs, corresponding to genuine variability in a system’s behaviour based on environmental factors. This language is then coupled with the LBUC spatio-temporal logic which combines Signal Temporal Logic (STL) temporal operators with an uncertain context operator which quantifies over an uncertain context model describing the range of environments over which a property must hold. We develop model-checking procedures for STL and LBUC properties based on verified signal monitoring over flowpipes produced by the Flow* verified integrator, including the technique of masking which directs monitoring for atomic propositions to time regions relevant to the overall verification problem at hand. This allows us to monitor many interesting nested contextual properties and frequently reduces monitoring costs by an order of magnitude. Finally, we explore the technique of contextual signal monitoring which can use a single Flow* flowpipe representing a functional dependency to complete a whole tree of signals corresponding to different uncertain contexts. This allows us to produce refined monitoring results over the whole space and to explore the variation in system behaviour in different contexts

Embedding requirements within the model driven architecture.

The Model Driven Architecture (MDA) is offered as one way forward in software systems modelling to connect software design with the business domain. The general focus of the MDA is the development of software systems by performing transformations between software design models, and the automatic generation of application code from those models. Software systems are provided by developers, whose experience and models are not always in line with those of other stakeholders, which presents a challenge for the community. From reviewing the available literature, it is found that whilst many models and notations are available, those that are significantly supported by the MDA may not be best for use by non technical stakeholders. In addition, the MDA does not explicitly consider requirements and specification. This research begins by investigating the adequacy of the MDA requirements phase and examining the feasibility of incorporating a requirements definition, specifically focusing upon model transformations. MDA artefacts were found to serve better the software community and requirements were not appropriately integrated within the MDA, with significant extension upstream being required in order to sufficiently accommodate the business user in terms of a requirements definition. Therefore, an extension to the MDA framework is offered that directly addresses Requirements Engineering (RE), including the distinction of analysis from design, highlighting the importance of specification. This extension is suggested to further the utility of the MDA by making it accessible to a wider audience upstream, enabling specification to be a direct output from business user involvement in the requirements phase of the MDA. To demonstrate applicability, this research illustrates the framework extension with the provision of a method and discusses the use of the approach in both academic and commercial settings. The results suggest that such an extension is academically viable in facilitating the move from analysis into the design of software systems, accessible for business use and beneficial in industry by allowing for the involvement of the client in producing models sufficient enough for use in the development of software systems using MDA tools and techniques

Second Generation General System Theory: Perspectives in Philosophy and Approaches in Complex Systems

Following the classical work of Norbert Wiener, Ross Ashby, Ludwig von Bertalanffy and many others, the concept of System has been elaborated in different disciplinary fields, allowing interdisciplinary approaches in areas such as Physics, Biology, Chemistry, Cognitive Science, Economics, Engineering, Social Sciences, Mathematics, Medicine, Artificial Intelligence, and Philosophy. The new challenge of Complexity and Emergence has made the concept of System even more relevant to the study of problems with high contextuality. This Special Issue focuses on the nature of new problems arising from the study and modelling of complexity, their eventual common aspects, properties and approaches—already partially considered by different disciplines—as well as focusing on new, possibly unitary, theoretical frameworks. This Special Issue aims to introduce fresh impetus into systems research when the possible detection and correction of mistakes require the development of new knowledge. This book contains contributions presenting new approaches and results, problems and proposals. The context is an interdisciplinary framework dealing, in order, with electronic engineering problems; the problem of the observer; transdisciplinarity; problems of organised complexity; theoretical incompleteness; design of digital systems in a user-centred way; reaction networks as a framework for systems modelling; emergence of a stable system in reaction networks; emergence at the fundamental systems level; behavioural realization of memoryless functions

The application of classical conditioning to the machine learning of a commonsense knowledge of visual events

In the field of artificial intelligence, possession of commonsense knowledge has long been considered to be a requirementto construct a machine that possesses artificial general intelligence. The conventional approach to providing this commonsense knowledge is to manually encode the required knowledge, a process that is both tedious and costly. After an analysis of classical conditioning, it was deemed that constructing a system based upon the stimulusstimulus interpretation of classical conditioning could allow for commonsense knowledge to be learned through a machine directly and passively observing its environment. Based upon these principles, a system was constructed that uses a stream of events, that have been observed within the environment, to learn rules regarding what event is likely to follow after the observation of another event. The system makes use of a feedback loop between three sub-systems: one that associates events that occur together, a second that accumulates evidence that a given association is significant and a third that recognises the significant associations. The recognition of past associations allows for both the creation of evidence for and against the existence of a particular association, and also allows for more complex associations to be created by treating instances of strongly associated event pairs to be themselves events. Testing the abilities of the system involved simulating the three different learning environments. The results found that measures of significance based on classical conditioning generally outperformed a probability-based measure. This thesis contributes a theory of how a stimulus-stimulus interpretation classical conditioning can be used to create commonsense knowledge and an observation that a significant sub-set of classical conditioning phenomena likely exist to aid in the elimination of noise. This thesis also represents a significant departure from existing reinforcement learning systems as the system presented in this thesis does not perform any form of action selection

Programming Languages and Systems

This open access book constitutes the proceedings of the 28th European Symposium on Programming, ESOP 2019, which took place in Prague, Czech Republic, in April 2019, held as Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2019