The use of Bayesian networks to determine software inspection process efficiency

Adherence to a defined process or standards is necessary to achieve satisfactory software quality. However, in order to judge whether practices are effective at achieving the required integrity of a software product, a measurement-based approach to the correctness of the software development is required. A defined and measurable process is a requirement for producing safe software productively. In this study the contribution of quality assurance to the software development process, and in particular the contribution that software inspections make to produce satisfactory software products, is addressed. I have defined a new model of software inspection effectiveness, which uses a Bayesian Belief Network to combine both subjective and objective data to evaluate the probability of an effective software inspection. Its performance shows an improvement over the existing published models of inspection effectiveness. These previous models made questionable assumptions over the distribution of errors and were essentially static. They could not make use of experience both in terms of process improvement and the increased experience of the inspectors. A sensitivity analysis of my model showed that it is consistent with the attributes which were thought important by Michael Fagan in his research into the software inspection method. The performance of my model show that it is an improvement over published models and over a multiple logistic regression model, which was formed using the same calibration data. By applying my model of software inspection effectiveness before the inspection takes place, project managers will be able to make better use of inspection resource available. Applying the model using data collected during the inspection will help in estimation of residual errors in a product. Decisions can then be made if further investigations are required to identify errors. The modelling process has been used successfully in an industrial application

An Empirical Study of a Software Maintenance Process

This paper describes how a process support tool is used to collect metrics about a major upgrade to our own electronic retail system. An incremental prototyping lifecycle is adopted in which each increment is categorised by an effort type and a project component. Effort types are Acquire, Build, Comprehend and Design and span all phases of development. Project components include data models and process models expressed in an OO modelling language and process algebra respectively as well as C++ classes and function templates and build components including source files and data files. This categorisation is independent of incremental prototyping and equally applicable to other software lifecycles. The process support tool (PWI) is responsible for ensuring the consistency between the models and the C++ source. It also supports the interaction between multiple developers and multiple metric-collectors. The first two releases of the retailing software are available for ftp from oracle.ecs.soton.ac.uk in directory pub/peter. Readers are invited to use the software and apply their own metrics as appropriate. We would be interested to correspond with anyone who does so

Advanced Techniques for Assets Maintenance Management

16th IFAC Symposium on Information Control Problems in Manufacturing INCOM 2018 Bergamo, Italy, 11–13 June 2018. Edited by Marco Macchi, László Monostori, Roberto PintoThe aim of this paper is to remark the importance of new and advanced techniques supporting decision making in different business processes for maintenance and assets management, as well as the basic need of adopting a certain management framework with a clear processes map and the corresponding IT supporting systems. Framework processes and systems will be the key fundamental enablers for success and for continuous improvement. The suggested framework will help to define and improve business policies and work procedures for the assets operation and maintenance along their life cycle. The following sections present some achievements on this focus, proposing finally possible future lines for a research agenda within this field of assets management

Using Counts as Heuristics for the Analysis of Static Models

The upstream activities of software development are often viewed as both the most important, in terms of cost, and the yet the least understood, and most problematic, particularly in terms of satisfying customer requirements. Business process modelling is one solution that is being increasingly used in conjunction with traditional software development, often feeding in to requirements and analysis activities. In addition, research in Systems Engineering for Business Process Change, highlights the importance of modelling business processes in evolving and maintaining the legacy systems that support those processes. However, the major use of business process modelling, is to attempt to restructure the business process, in order to improve some given aspect, e.g., cost or time. This restructuring may be seen either as separate activity or as a pre-cursor to the development of systems to support the new or improved process. Hence, the analysis of these business models is vital to the improvement of the process, and as a consequence to the development of supporting software systems. Supporting this analysis is the focus of this paper. Business processes are typically described with static (diagrammatic) models. This paper proposes the use of measures (counts) to aid analysis and comparison of these static process descriptions. The proposition is illustrated by showing how measures can be applied to a commonly used process-modelling notation, Role Activity Diagrams (RADs). Heuristics for RADs are described and measures suggested which support those heuristics. An example process is used to show how a coupling measure can be used to highlight features in RADs useful to the process modeller. To fully illustrate the proposition the paper describes and applies a framework for the theoretical validation of the coupling measure. An empirical evaluation follows. This is illustrated by two case studies; the first based on the bidding process of a large telecommunications systems supplier, and the second a study of ten prototyping processes across a number of organisations. These studies found that roles of the same type exhibited similar levels of coupling across processes. Where roles did not adhere to tentative threshold values, further investigation revealed unusual circumstances or hidden behaviour. Notably, study of the prototyping roles, which exhibited the greatest variation in coupling, found that coupling was highly correlated with the size of the development team. This suggests that prototyping in large projects had a different process to that for small projects, using more mechanisms for communication. Hence, the empirical studies support the view that counts (measures) may be useful in the analysis of static process models

The development and testing of a contextual model for healthcare quality improvement using Lean and the Model for Understanding Success in Quality (MUSIQ) : a thesis presented in partial fulfilment of the requirements for the degree of Master of Quality Systems at Massey University, Palmerston North, New Zealand

This study developed a new theoretical model of quality improvement (QI) contextual factors, for QI activity undertaken at the healthcare microsystem level. The Model for Understanding Success in Quality (MUSIQ) (Kaplan, Provost, Froehle, & Margolis, 2012), was aligned with Lean improvement activity using the Toyota Way framework. The aim of the research was to improve the effectiveness of healthcare quality improvement initiatives by providing more understanding of the associations, relative importance and precise functioning of critical contextual factors. A new survey instrument, based on the literature, was developed to collect data and the hypothesised theoretical relationships were tested using the partial least squares path modelling (PLSPM) technique. QI practitioners at a large New Zealand District Health Board were surveyed on a range of contextual factors hypothesised to influence improvement outcomes. All survey participants had recently completed a small-scale improvement project using Lean, or were participants in training programmes that introduced them to Lean thinking and methods. Some participants worked autonomously on improvements of their own selection; others were part of a wider training programme derived from the National Health Service’s (UK) ‘productive ward’ programme. In the healthcare organisational context, the majority of these improvement initiatives were carried out at the microsystem level – initiated and delivered by the teams responsible for the work processes being modified. Survey responses were first analysed via principal components analysis (to examine the dimensionality of the scales) and then PLSPM. The defined contextual factors for ‘Teamwork’, ‘Respect for People’, ‘Lean Actions’ and the influence of negatively motivating factors all reached significance. Defined contextual factors for ‘Previous Experience’ and the influence of positive motivating factors did not reach significance at 5% level. The final model showed a statistically significant, moderate predictive strength, with an overall adjusted R2 of 0.58. This result was an encouraging validation of the microsystem-level layer of the MUSIQ model using Lean as the QI method (context). The relative influence of ‘Teamwork’, ‘Respect for People’, ‘Motivation’, and a mediating mechanism for making process changes (in this instance, Lean) were measured and found to be consistent with the MUSIQ model. Identifying more detailed causal mechanisms (the present model was intentionally parsimonious due to the time frame allowed and the resources available for the research), refining the operational definitions, and developing and testing predictive models for the defined contextual factors are the proposed next steps in the research