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Designing information systems requirements in context: Insights from the theory of deferred action
This paper considers conceptual and contextual issues relating to the problem of
developing systems models capable of representing knowable and unknowable
information requirements. It postulates that the systemic emergence property of
systems is the cause of unknowable organisational information requirements. The
Theory of Deferred Action and its systems constructs are invoked to explain
emergence and how it can be modelled in formal systems. The insights proposed are
believed to assist designers in developing functional and relevant approaches within
dynamic organisational contexts
Deferred Action: Theoretical model of process architecture design for emergent business processes
E-Business modelling and ebusiness systems development assumes fixed company resources,
structures, and business processes. Empirical and theoretical evidence suggests that company resources
and structures are emergent rather than fixed. Planning business activity in emergent contexts requires
flexible ebusiness models based on better management theories and models . This paper builds and
proposes a theoretical model of ebusiness systems capable of catering for emergent factors that affect
business processes. Drawing on development of theories of the âaction and designâclass the Theory of
Deferred Action is invoked as the base theory for the theoretical model. A theoretical model of flexible
process architecture is presented by identifying its core components and their relationships, and then
illustrated with exemplar flexible process architectures capable of responding to emergent factors.
Managerial implications of the model are considered and the modelâs generic applicability is discussed
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Towards a theory of software engineering
A theory of software engineering (SE) is presented and its application to explaining and analysing SE situations is illustrated. The theory is based on a characterization of SE representations and the fundamental activities that are applied to them. Motivations for developing a theory and means of establishing its validity are also discussed
Adaptive Process Management in Cyber-Physical Domains
The increasing application of process-oriented approaches in new challenging cyber-physical domains beyond business computing (e.g., personalized healthcare, emergency management, factories of the future, home automation, etc.) has led to reconsider the level of flexibility and support required to manage complex processes in such domains. A cyber-physical domain is characterized by the presence of a cyber-physical system coordinating heterogeneous ICT components (PCs, smartphones, sensors, actuators) and involving real world entities (humans, machines, agents, robots, etc.) that perform complex tasks in the âphysicalâ real world to achieve a common goal. The physical world, however, is not entirely predictable, and processes enacted in cyber-physical domains must be robust to unexpected conditions and adaptable to unanticipated exceptions. This demands a more flexible approach in process design and enactment, recognizing that in real-world environments it is not adequate to assume that all possible recovery activities can be predefined for dealing with the exceptions that can ensue. In this chapter, we tackle the above issue and we propose a general approach, a concrete framework and a process management system implementation, called SmartPM, for automatically adapting processes enacted in cyber-physical domains in case of unanticipated exceptions and exogenous events. The adaptation mechanism provided by SmartPM is based on declarative task specifications, execution monitoring for detecting failures and context changes at run-time, and automated planning techniques to self-repair the running process, without requiring to predefine any specific adaptation policy or exception handler at design-time
Formalising the Continuous/Discrete Modeling Step
Formally capturing the transition from a continuous model to a discrete model
is investigated using model based refinement techniques. A very simple model
for stopping (eg. of a train) is developed in both the continuous and discrete
domains. The difference between the two is quantified using generic results
from ODE theory, and these estimates can be compared with the exact solutions.
Such results do not fit well into a conventional model based refinement
framework; however they can be accommodated into a model based retrenchment.
The retrenchment is described, and the way it can interface to refinement
development on both the continuous and discrete sides is outlined. The approach
is compared to what can be achieved using hybrid systems techniques.Comment: In Proceedings Refine 2011, arXiv:1106.348
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