A systematic approach to atomicity decomposition in Event-B

Event-B is a state-based formal method that supports a refinement process in which an abstract model is elaborated towards an implementation in a step-wise manner. One weakness of Event-B is that control flow between events is typically modelled implicitly via variables and event guards. While this fits well with Event-B refinement, it can make models involving sequencing of events more difficult to specify and understand than if control flow was explicitly specified. New events may be introduced in Event-B refinement and these are often used to decompose the atomicity of an abstract event into a series of steps. A second weakness of Event-B is that there is no explicit link between such new events that represent a step in the decomposition of atomicity and the abstract event to which they contribute. To address these weaknesses, atomicity decomposition diagrams support the explicit modelling of control flow and refinement relationships for new events. In previous work,the atomicity decomposition approach has been evaluated manually in the development of two large case studies, a multi media protocol and a spacecraft sub-system. The evaluation results helped us to develop a systematic definition of the atomicity decomposition approach, and to develop a tool supporting the approach. In this paper we outline this systematic definition of the approach, the tool that supports it and evaluate the contribution that the tool makes

Modelling flexible manufacturing systems through discrete event simulation

As customisation and product diversification are becoming standard, industry is looking for strategies to become more adaptable in responding to customer’s needs. Flexible manufacturing systems (FMS) provide a unique capability where there is a need to provide efficiency through production flexibility. Full potential of FMS development is difficult to achieve due to the variability of components within this complex manufacturing system. It has been recognised that there is a requirement for decision support tools to address different aspects of FMS development. Discrete event simulation (DES) is the most common tool used in manufacturing sector for solving complex problems. Through systematic literature review, the need for a conceptual framework for decision support in FMS using DES has been identified. Within this thesis, the conceptual framework (CF) for decision support for FMS using DES has been proposed. The CF is designed based on decision-making areas identified for FMS development in literature and through industry stakeholder feedback: set-up, flexibility and schedule configuration. The CF has been validated through four industrial simulation case studies developed as a part of implementation of a new FMS plant in automotive sector. The research focuses on: (1) a method for primary data collection for simulation validated through a case study of material handling robot behaviour in FMS; (2) an approach for evaluation of optimal production set-up for industrial FMS with DES; (3) a DES based approach for testing FMS flexibility levels; (4) an approach for testing scheduling in FMS with the use of DES. The study has supported the development of systematic approach for decision making in FMS development using DES. The approach provided tools for evidence based decision making in FMS

Learn or Earn? - Intelligent Task Recommendation for Competitive Crowdsourced Software Development

Background: Competitive crowdsourced development encourages online software developers to register for tasks offered on the crowdsourcing platform and implement them in a competitive mode. As a large number of tasks are uploaded daily, the scenery of competition is changing continuously. Without appropriate decision support, online developers often make task decisions in an ad hoc and intuitive manner. Aims: To provide dynamic decision support for crowd developers to select the task that fit best to their personal learning versus earning objectives, taking into account the actual competitiveness situation. Method: We propose a recommendation system called EX2 ( EX-Square ) that combines both explorative ( learn ) and exploitative ( earn ) search for tasks, based on a systematic analysis of workers preference patterns, technologies hotness, and the projection of winning chances. The implemented prototype allows dynamic recommendations that reflect task updates and competition dynamics at any given time. Results: Based on evaluation from 4007 tasks monitored over a period of 2 years, we show that EX2 can explore and adjust task recommendations corresponding to context changes, and individual learning preferences of workers. A survey was also conducted with 14 actual crowd workers, showing that intelligent decision support from EX2 is considered useful and valuable. Conclusions: With support from EX2, workers benefit from the tool from getting customized recommendations, and the platform provider gets a higher chance to better cover the breadth of technology needs in case recommendations are taken

Software Reuse in Agile Development Organizations - A Conceptual Management Tool

The reuse of knowledge is considered a major factor for increasing productivity and quality. In the software industry knowledge is embodied in software assets such as code components, functional designs and test cases. This kind of knowledge reuse is also referred to as software reuse. Although the benefits can be substantial, software reuse has never reached its full potential. Organizations are not aware of the different levels of reuse or do not know how to address reuse issues. This paper proposes a conceptual management tool for supporting software reuse. Furthermore the paper presents the findings of the application of the management tool in an agile development organization

How to discriminate between computer-aided and computer-hindered decisions: a case study in mammography

Background. Computer aids can affect decisions in complex ways, potentially even making them worse; common assessment methods may miss these effects. We developed a method for estimating the quality of decisions, as well as how computer aids affect it, and applied it to computer-aided detection (CAD) of cancer, reanalyzing data from a published study where 50 professionals (“readers”) interpreted 180 mammograms, both with and without computer support. Method. We used stepwise regression to estimate how CAD affected the probability of a reader making a correct screening decision on a patient with cancer (sensitivity), thereby taking into account the effects of the difficulty of the cancer (proportion of readers who missed it) and the reader’s discriminating ability (Youden’s determinant). Using regression estimates, we obtained thresholds for classifying a posteriori the cases (by difficulty) and the readers (by discriminating ability). Results. Use of CAD was associated with a 0.016 increase in sensitivity (95% confidence interval [CI], 0.003–0.028) for the 44 least discriminating radiologists for 45 relatively easy, mostly CAD-detected cancers. However, for the 6 most discriminating radiologists, with CAD, sensitivity decreased by 0.145 (95% CI, 0.034–0.257) for the 15 relatively difficult cancers. Conclusions. Our exploratory analysis method reveals unexpected effects. It indicates that, despite the original study detecting no significant average effect, CAD helped the less discriminating readers but hindered the more discriminating readers. Such differential effects, although subtle, may be clinically significant and important for improving both computer algorithms and protocols for their use. They should be assessed when evaluating CAD and similar warning systems

Development of Hospice Environmental Assessment Protocol (HEAP): A Post Occupancy Evaluation Tool

The post-occupancy evaluation (POE) of any building facility is essential for providing feedback to the architects and to the building owners for further improvement in design skills and management procedures. Since the 1990s several POE tools have been developed focusing on nursing home environments, but no POE tool has been developed for hospice environments. Generally, the nursing home POE tool has been used to assess hospice facilities, but in recent studies, a significant gap has been found in the usefulness because hospice patients are mostly bed-bound, their physical, social and spiritual demands are different, and a patient’s family accommodation plays a significant role in the patient’s dying experience. The need of developing a POE tool for hospice facilities is evident, and this study has focused on fulfilling that goal. To develop an indicative level of POE tool for hospice, the Professional Environmental Assessment Protocol (PEAP) was selected as a precedent model. PEAP was developed to provide a standardized method of expert evaluation of special-care units for people with dementia, and it not only assesses the physical setting but also includes some assessment of organizational and policy features of the environment. This doctoral thesis developed the Hospice Environmental Assessment Protocol (HEAP), which assesses only the physical setting and does not include assessment processes of organizational or policy features. It involved three research objectives: a) to identify the ‘Therapeutic Goals (TGs)’ of hospice environments; b) to develop a list of design considerations for each therapeutic goal, and c) to develop an evaluation matrix and a descriptive five-point rating scale for each goal. The qualitative research design was considered using three methods: a) a systematic literature review to identify TGs; b) the Delphi method to obtain expert opinions, and c) five case study surveys. HEAP provides a standardized method to evaluate building performance based on eleven TGs; provide continuity of self, provide access to nature, provide privacy, facilitate social interaction, maximize safety and security, provide autonomy, regulate stimulation and support sensory therapies, provide spiritual care, provide family accommodation, provide support after death, and maximize support for staff

A model-driven method for the systematic literature review of qualitative empirical research

This paper explores a model-driven method for systematic literature reviews (SLRs), for use where the empirical studies found in the literature search are based on qualitative research. SLRs are an important component of the evidence-based practice (EBP) paradigm, which is receiving increasing attention in information systems (IS) but has not yet been widely-adopted. We illustrate the model-driven approach to SLRs via an example focused on the use of BPMN (Business Process Modelling Notation) in organizations. We discuss in detail the process followed in using the model-driven SLR method, and show how it is based on a hermeneutic cycle of reading and interpreting, in order to develop and refine a model which synthesizes the research findings of previous qualitative studies. This study can serve as an exemplar for other researchers wishing to carry out model-driven SLRs. We conclude with our reflections on the method and some suggestions for further researc

Research Findings on Empirical Evaluation of Requirements Specifications Approaches

Numerous software requirements specification (SRS) approaches have been proposed in software engineering. However, there has been little empirical evaluation of the use of these approaches in specific contexts. This paper describes the results of a mapping study, a key instrument of the evidence-based paradigm, in an effort to understand what aspects of SRS are evaluated, in which context, and by using which research method. On the basis of 46 identified and categorized primary studies, we found that understandability is the most commonly evaluated aspect of SRS, experiments are the most commonly used research method, and the academic environment is where most empirical evaluation takes place