Cost-benefit modelling for reliability growth

Decisions during the reliability growth development process of engineering equipment involve trade-offs between cost and risk. However slight, there exists a chance an item of equipment will not function as planned during its specified life. Consequently the producer can incur a financial penalty. To date, reliability growth research has focussed on the development of models to estimate the rate of failure from test data. Such models are used to support decisions about the effectiveness of options to improve reliability. The extension of reliability growth models to incorporate financial costs associated with 'unreliability' is much neglected. In this paper, we extend a Bayesian reliability growth model to include cost analysis. The rationale of the stochastic process underpinning the growth model and the cost structures are described. The ways in which this model can be used to support cost-benefit analysis during product development are discussed and illustrated through a simple case

Generic unified modelling process for developing semantically rich, dynamic and temporal models

Models play a vital role in supporting a range of activities in numerous domains. We rely on models to support the design, visualisation, analysis and representation of parts of the world around us, and as such significant research effort has been invested into numerous areas of modelling; including support for model semantics, dynamic states and behaviour, temporal data storage and visualisation. Whilst these efforts have increased our capabilities and allowed us to create increasingly powerful software-based models, the process of developing models, supporting tools and /or data structures remains difficult, expensive and error-prone. In this paper we define from literature the key factors in assessing a model’s quality and usefulness: semantic richness, support for dynamic states and object behaviour, temporal data storage and visualisation. We also identify a number of shortcomings in both existing modelling standards and model development processes and propose a unified generic process to guide users through the development of semantically rich, dynamic and temporal models

A model driven approach for software systems reliability

The reliability assurance of software systems from design to deployment level through transformation techniques and model driven approach, is described. Once the reliability mechanisms provided by current component-based development architectures (CBDA) are designed in a platform-independent way, platform-based design and implementation models must be extended. Current CBDAs, such as Enterprise Java Beans, address a considerable range of features to support system reliability. The evaluation aims to test maturity of the approach, its applicability, and the effectiveness of reliability models. The techniques such as process algebras are generally considered time consuming, in regard to software development

A knowledge development lifecycle for reflective practice

Reflective practice is valuable because of its potential for continuous improvement through feedback and learning. Conventional models of knowledge practice however do not explicitly include reflection as part of the practice, nor locate it in a developmental cycle. They focus on modelling in a knowledge plane which itself is contextualised by active knowing processes, and ignore the influence of power in their activity models. Further, many models focus on either an artefact or a process view, resulting from a conceptual disconnect between knowledge and knowing, and failure to relate passive to active views. Using the idea of higher order loops that govern knowledge development processes, in this paper we propose a conceptualisation of a reflective Knowledge Development Life Cycle (KDLC). This explicitly includes the investigator and the organisation itself as dynamic components of a systemic process and is suited to either a constructivist or realist epistemological stance. We describe the stages required in the KDLC and discuss their significance. Finally we show how incorporation of reflection into process enables dynamic interplay between the knowing and the knowledge in the organisation

The impact of resources on decision making

Decision making is a significant activity within industry and although much attention has been paid to the manner in which goals impact on how decision making is executed, there has been less focus on the impact decision making resources can have. This article describes an experiment that sought to provide greater insight into the impact that resources can have on how decision making is executed. Investigated variables included the experience levels of decision makers and the quality and availability of information resources. The experiment provided insights into the variety of impacts that resources can have upon decision making, manifested through the evolution of the approaches, methods, and processes used within it. The findings illustrated that there could be an impact on the decision-making process but not on the method or approach, the method and process but not the approach, or the approach, method, and process. In addition, resources were observed to have multiple impacts, which can emerge in different timescales. Given these findings, research is suggested into the development of resource-impact models that would describe the relationships existing between the decision-making activity and resources, together with the development of techniques for reasoning using these models. This would enhance the development of systems that could offer improved levels of decision support through managing the impact of resources on decision making

An Embedded Domain Specific Language to Model, Transform and Quality Assure Business Processes in Business-Driven Development

In Business-Driven Development (BDD), business process models are produced by business analysts. To ensure that the business requirements are satisfied, the IT solution is directly derived through a process of model refinement. If models do not contain all the required technical details or contain errors, the derived implementation would be incorrect and the BDD lifecycle would have to be repeated. In this project we present a functional domain specific language embedded in Haskell, with which: 1) models can rapidly be produced in a concise and abstract manner, 2) enables focus on the specifications rather than the implementation, 3) ensures that all the required details, to generate the executable code, are specified, 4) models can be transformed, analysed and interpreted in various ways, 5) quality assures models by carrying out three types of checks; by Haskell.s type checker, at construction-time and by functions that analyse the soundness of models, 6) enables users to define quality assured composite model transformations

The Tropos Software Development Methodology: Processes, Models and Diagrams

Tropos is a novel agent-oriented software development methodology founded on two key features: (i) the notions of agent, goal, plan and various other knowledge level concepts are fundamental primitives used uniformly throughout the software development process; and (ii) a crucial role is assigned to requirements analysis and specification when the system-to-be is analyzed with respect to its intended environment. This paper provides a (first) detailed account of the Tropos methodology. In particular, we describe the basic concepts on which Tropos is founded and the types of models one builds out of them. We also specify the analysis process through which design flows from external to system actors through a goal analysis and delegation. In addition, we provide an abstract syntax for Tropos diagrams and other linguistic constructs

Modelling and analysing user views of telecommunications services

User views of calls are modelled by behaviour trees, which are synchronised to form a network of users. High level presentations of the models are given using process algebra and an explicit theory of features, including precedences. These precedences abstractly encapsulate the possible state spaces which result from different combinations of features. The high level presentation supports incremental development of features and testing and experimentation through animation. Interactions which are not detected during the experimentation phase may be found through static analysis of the high level presentation, through dynamic analysis of the under-lying low level transition system, and through verification of temporal properties through model-checking. In each case, interactions are resolved through manipulation of the feature precedences