An Exploration of parametric software cost estimating models for Jackson Systems Development

Most parametric software cost estimation models used today evolved in the late 70's and early 80's. At that time, the dominant software development techniques being used were the early 'structured methods'. Since then, several new systems development paradigms and methods have emerged, one being Jackson Systems Development (JSD). As current cost estimating methods do not take account of these developments, their non-universality means they cannot provide adequate estimates of effort and hence cost. In order to address these shortcomings two new estimation methods have been developed for JSD projects. One of these methods JSD-FPA, is a top-down estimating method, based on the existing MKII function point method. The other method, JSD-COCOMO, is a sizing technique which sizes a project, in terms of lines of code, from the process structure diagrams and thus provides an input to the traditional COCOMO method.The JSD-FPA method allows JSD projects in both the real-time and scientific application areas to be costed, as well as the commercial information systems applications to which FPA is usually applied. The method is based upon a three-dimensional view of a system specification as opposed to the largely data-oriented view traditionally used by FPA. The method uses counts of various attributes of a JSD specification to develop a metric which provides an indication of the size of the system to be developed. This size metric is then transformed into an estimate of effort by calculating past project productivity and utilising this figure to predict the effort and hence cost of a future project. The effort estimates produced were validated by comparing them against the effort figures for six actual projects.The JSD-COCOMO method uses counts of the levels in a process structure chart as the input to an empirically derived model which transforms them into an estimate of delivered source code instructions.

The transformational implementation of JSD process specifications via finite automata representation

Conventional structured methods of software engineering are often based on the use of functional decomposition coupled with the Waterfall development process model. This approach is argued to be inadequate for coping with the evolutionary nature of large software systems. Alternative development paradigms, including the operational paradigm and the transformational paradigm, have been proposed to address the inadequacies of this conventional view of software developement, and these are reviewed. JSD is presented as an example of an operational approach to software engineering, and is contrasted with other well documented examples. The thesis shows how aspects of JSD can be characterised with reference to formal language theory and automata theory. In particular, it is noted that Jackson structure diagrams are equivalent to regular expressions and can be thought of as specifying corresponding finite automata. The thesis discusses the automatic transformation of structure diagrams into finite automata using an algorithm adapted from compiler theory, and then extends the technique to deal with areas of JSD which are not strictly formalisable in terms of regular languages. In particular, an elegant and novel method for dealing with so called recognition (or parsing) difficulties is described,. Various applications of the extended technique are described. They include a new method of automatically implementing the dismemberment transformation; an efficient way of implementing inversion in languages lacking a goto-statement; and a new in-the-large implementation strategy.

Structured neural network modelling of multi-valued functions for wind retrieval from scatterometer measurements

A conventional neural network approach to regression problems approximates the conditional mean of the output vector. For mappings which are multi-valued this approach breaks down, since the average of two solutions is not necessarily a valid solution. In this article mixture density networks, a principled method to model conditional probability density functions, are applied to retrieving Cartesian wind vector components from satellite scatterometer data. A hybrid mixture density network is implemented to incorporate prior knowledge of the predominantly bimodal function branches. An advantage of a fully probabilistic model is that more sophisticated and principled methods can be used to resolve ambiguities.

Structured neural network modelling of multi-valued functions for wind retrieval from scatterometer measurements

A conventional neural network approach to regression problems approximates the conditional mean of the output vector. For mappings which are multi-valued this approach breaks down, since the average of two solutions is not necessarily a valid solution. In this article mixture density networks, a principled method to model conditional probability density functions, are applied to retrieving Cartesian wind vector components from satellite scatterometer data. A hybrid mixture density network is implemented to incorporate prior knowledge of the predominantly bimodal function branches. An advantage of a fully probabilistic model is that more sophisticated and principled methods can be used to resolve ambiguities.

Practices and views on fetal heart monitoring:A structured observation and interview study

Objective: To assess and explain deviations from recommended practice in National Institute for Clinical Excellence (NICE) guidelines in relation to fetal heart monitoring. Design: Qualitative study. Setting: Large teaching hospital in the UK. Sample: Sixty-six hours of observation of 25 labours and interviews with 20 midwives of varying grades. Methods: Structured observations of labour and semistructured interviews with midwives. Interviews were undertaken using a prompt guide, audiotaped, and transcribed verbatim. Analysis was based on the constant comparative method, assisted by QSR N5 software. Main outcome measures: Deviations from recommended practice in relation to fetal monitoring and insights into why these occur. Results: All babies involved in the study were safely delivered, but 243 deviations from recommended practice in relation to NICE guidelines on fetal monitoring were identified, with the majority (80%) of these occurring in relation to documentation. Other deviations from recommended practice included indications for use of electronic fetal heart monitoring and conduct of fetal heart monitoring. There is evidence of difficulties with availability and maintenance of equipment, and some deficits in staff knowledge and skill. Differing orientations towards fetal monitoring were reported by midwives, which were likely to have impacts on practice. The initiation, management, and interpretation of fetal heart monitoring is complex and distributed across time, space, and professional boundaries, and practices in relation to fetal heart monitoring need to be understood within an organisational and social context. Conclusion: Some deviations from best practice guidelines may be rectified through straightforward interventions including improved systems for managing equipment and training. Other deviations from recommended practice need to be understood as the outcomes of complex processes that are likely to defy easy resolution. © RCOG 2006.

Spatially structured cognitve models of semantic information:the implications for computerised databases

Existing theories of semantic cognition propose models of cognitive processing occurring in a conceptual space, where ‘meaning’ is derived from the spatial relationships between concepts’ mapped locations within the space. Information visualisation is a growing area of research within the field of information retrieval, and methods for presenting database contents visually in the form of spatial data management systems (SDMSs) are being developed. This thesis combined these two areas of research to investigate the benefits associated with employing spatial-semantic mapping (documents represented as objects in two- and three-dimensional virtual environments are proximally mapped dependent on the semantic similarity of their content) as a tool for improving retrieval performance and navigational efficiency when browsing for information within such systems. Positive effects associated with the quality of document mapping were observed; improved retrieval performance and browsing behaviour were witnessed when mapping was optimal. It was also shown using a third dimension for virtual environment (VE) presentation provides sufficient additional information regarding the semantic structure of the environment that performance is increased in comparison to using two-dimensions for mapping. A model that describes the relationship between retrieval performance and browsing behaviour was proposed on the basis of findings. Individual differences were not found to have any observable influence on retrieval performance or browsing behaviour when mapping quality was good. The findings from this work have implications for both cognitive modelling of semantic information, and for designing and testing information visualisation systems. These implications are discussed in the conclusions of this work.

Appraising qualitative research for inclusion in systematic reviews:A quantitative and qualitative comparison of three methods

Objective: Qualitative research is increasingly valued as part of the evidence for policy and practice, but how it should be appraised is contested. Various appraisal methods, including checklists and other structured approaches, have been proposed but rarely evaluated. We aimed to compare three methods for appraising qualitative research papers that were candidates for inclusion in a systematic review of evidence on support for breast-feeding. Method: A sample of 12 research papers on support for breast-feeding was appraised by six qualitative reviewers using three appraisal methods: unprompted judgement, based on expert opinion; a UK Cabinet Office quality framework; and CASP, a Critical Appraisal Skills Programme tool. Papers were assigned, following appraisals, to 1 of 5 categories, which were dichotomized to indicate whether or not papers should be included in a systematic review. Patterns of agreement in categorization of papers were assessed quantitatively using κ statistics, and qualitatively using cross-case analysis. Results: Agreement in categorizing papers across the three methods was slight (κ =0.13; 95% CI 0.06-0.24). Structured approaches did not appear to yield higher agreement than that by unprompted judgement. Qualitative analysis revealed reviewers' dilemmas in deciding between the potential impact of findings and the quality of the research execution or reporting practice. Structured instruments appeared to make reviewers more explicit about the reasons for their judgements. Conclusions: Structured approaches may not produce greater consistency of judgements about whether to include qualitative papers in a systematic review. Future research should address how appraisals of qualitative research should be incorporated in systematic reviews. © The Royal Society of Medicine Press Ltd 2007.

Projection and interpolation based techniques for structured and impulsive noise filtering

In this chapter we present the relevant mathematical background to address two well defined signal and image processing problems. Namely, the problem of structured noise filtering and the problem of interpolation of missing data. The former is addressed by recourse to oblique projection based techniques whilst the latter, which can be considered equivalent to impulsive noise filtering, is tackled by appropriate interpolation methods.

Investigating mental health risk assessment in primary care and the potential role of a structured decision support tool, GRiST

Aim: To explore current risk assessment processes in general practice and Improving Access to Psychological Therapies (IAPT) services, and to consider whether the Galatean Risk and Safety Tool (GRiST) can help support improved patient care. Background: Much has been written about risk assessment practice in secondary mental health care, but little is known about how it is undertaken at the beginning of patients' care pathways, within general practice and IAPT services. Methods: Interviews with eight general practice and eight IAPT clinicians from two primary care trusts in the West Midlands, UK, and eight service users from the same region. Interviews explored current practice and participants' views and experiences of mental health risk assessment. Two focus groups were also carried out, one with general practice and one with IAPT clinicians, to review interview findings and to elicit views about GRiST from a demonstration of its functionality. Data were analysed using thematic analysis. Findings Variable approaches to mental health risk assessment were observed. Clinicians were anxious that important risk information was being missed, and risk communication was undermined. Patients felt uninvolved in the process, and both clinicians and patients expressed anxiety about risk assessment skills. Clinicians were positive about the potential for GRiST to provide solutions to these problems. Conclusions: A more structured and systematic approach to risk assessment in general practice and IAPT services is needed, to ensure important risk information is captured and communicated across the care pathway. GRiST has the functionality to support this aspect of practice.

Description and preliminary results from a structured specialist behavioural weight management group intervention:Specialist Lifestyle Management (SLiM) programme

Background -  Specialist Lifestyle Management (SLiM) is a structured patient education and self-management group weight management programme. Each session is run monthly over a 6-month period providing a less intensive long-term approach. The groups are patient-centred incorporating educational, motivational, behavioural and cognitive elements. The theoretical background, programme structure and preliminary results of SLiM are presented. Subjects/methods - The study was a pragmatic service evaluation of obese patients with a body mass index (BMI) ≥35 kg/m2 with comorbidity or ≥40 kg/m2 without comorbidity referred to a specialist weight management service in the West Midlands, UK. 828 patients were enrolled within SLiM over a 48-month period. Trained facilitators delivered the programme. Preliminary anonymised data were analysed using the intention-to-treat principle. The primary outcome measure was weight loss at 3 and 6 months with comparisons between completers and non-completers performed. The last observation carried forward was used for missing data. Results - Of the 828 enrolled within SLiM, 464 completed the programme (56%). The mean baseline weight was 135 kg (BMI=49.1 kg/m2) with 87.2% of patients having a BMI≥40 kg/m2 and 12.4% with BMI≥60 kg/m2. The mean weight change of all patients enrolled was −4.1 kg (95% CI −3.6 to −4.6 kg, p=0.0001) at the end of SLiM, with completers (n=464) achieving −5.5 kg (95% CI −4.2 to −6.2 kg, p=0.0001) and non-completers achieving −2.3 kg (p=0.0001). The majority (78.6%) who attended the 6-month programme achieved weight loss with 32.3% achieving a ≥5% weight loss. Conclusions - The SLiM programme is an effective group intervention for the management of severe and complex obesity.

Comparison of weight loss outcomes between obese patients with and without Type 2 diabetes attending a weight management focused structured educational group

Aims: Specialist lifestyle management (SLiM) is a medically supported dietetically led structured group education and self-management programme focusing on weight management. Obese patients with Type 2 diabetes are perceived to find it more difficult to lose weight compared with those without diabetes. We aimed to compare the weight loss achieved by obese patients with or without Type 2 diabetes completing the SLiM programme. Methods: A prospective analysis of patients attending SLiM between 2009 and 2013 was conducted. Results: There were 454 obese patients (mean age 49.1 ± 11.6years, women 72.5%, body mass index 49.8 ± 9.3kg/m2, weight137.3 ± 28kg). 152/454 patients (33%) had Type 2 diabetes of which 31 (20.4%) were insulin treated. Patients with Type 2diabetes were older (52.4 ± 11.3 vs 47.5 ± 11.4 years, p < 0.001). SLiM resulted in significant weight loss in patients with (136.5 ± 27 vs 130.2 ± 25.3, p < 0.001) or without (137.6 ± 29 vs 132.6 ± 28.4, p < 0.001) Type 2 diabetes. Weight loss was comparable between patients with and without Type 2 diabetes (6.1 ± 7.9 vs5.1 ± 7kg, p = 0.2). The proportion of patients achieving ≥ 10%weight loss was similar between patients with and without Type 2diabetes (10.5% vs 9.9%, p = 0.4). Insulin-treated patients lost similar weight to those not treated with insulin (6.3 ± 9.4 vs 6.1 ± 7.6kg, p = 0.9). After adjustment for age, sex, referral weight and medications, Type 2 diabetes did not predict weight change during the SLiM programme (b = 0.3, p = 0.5). Conclusions: Attending the SLiM groups produces a significant weight loss in patients with Type 2 diabetes which is comparable to those without Type 2 diabetes. Insulin-treated patients lost similar weight to those not on insulin. Weight gain with Type 2 diabetes and insulin treatment is not ‘unavoidable’ if patients receive the appropriate support and education.