The Law Commission presumption concerning the dependability of computer evidence

We consider the condition set out in section 69(1)(b) of the Police and Criminal Evidence Act 1984 (PACE 1984) that reliance on computer evidence should be subject to proof of its correctness, and compare it to the 1997 Law Commission recommendation that acommon law presumption be used that a computer operated correctly unless there is explicit evidence to the contrary (LC Presumption). We understand the LC Presumption prevails in current legal proceedings. We demonstrate that neither section 69(1)(b) of PACE 1984 nor the LC presumption reflects the reality of general software-based system behaviour

A FRAMEWORK FOR SOFTWARE RELIABILITY MANAGEMENT BASED ON THE SOFTWARE DEVELOPMENT PROFILE MODEL

Recent empirical studies of software have shown a strong correlation between change history of files and their fault-proneness. Statistical data analysis techniques, such as regression analysis, have been applied to validate this finding. While these regression-based models show a correlation between selected software attributes and defect-proneness, in most cases, they are inadequate in terms of demonstrating causality. For this reason, we introduce the Software Development Profile Model (SDPM) as a causal model for identifying defect-prone software artifacts based on their change history and software development activities. The SDPM is based on the assumption that human error during software development is the sole cause for defects leading to software failures. The SDPM assumes that when a software construct is touched, it has a chance to become defective. Software development activities such as inspection, testing, and rework further affect the remaining number of software defects. Under this assumption, the SDPM estimates the defect content of software artifacts based on software change history and software development activities. SDPM is an improvement over existing defect estimation models because it not only uses evidence from current project to estimate defect content, it also allows software managers to manage software projects quantitatively by making risk informed decisions early in software development life cycle. We apply the SDPM in several real life software development projects, showing how it is used and analyzing its accuracy in predicting defect-prone files and compare the results with the Poisson regression model

Modelling condition monitoring inspection using the delay-time concept

In the literature on inspection modelling, the failure distribution traditionally plays a fundamental role in model construction in that it is assumed that system failures occur instantly at random time points from new with a known pdf. of time to failure. Numerous models have been built on this basis. However, Professor Christer challenged this traditional idea and proposed the concept of delay time. The idea, which is an essential part of most engineers' experience, assumes that defects do not just appear as failures, but are present for a while before becoming sufficiently obvious to be noticed and declared as failures. The time lapse from when a defect could first be identified at an inspection to consequential failure has been termed the "delay time". It is this idea which can be captured to reveal the nature and scope for preventive maintenance or inspection. It appears that the concept is now being taken up by many other authors. In this thesis, various models for condition monitoring inspection are built on the basis of delay time analysis. Extensions and further developments are made here to enrich the delay-time modelling. Since the distribution of the delay time is important to delay time modelling, a new approach to estimate the delay time distribution is proposed. This technique, which contrasts with the previous subjective data estimation technique, is based upon objective data. Assuming the distribution of the delay time is known, models of condition monitoring inspection are fully discussed for both perfect and imperfect inspections, and for infinite and finite time horizons. Based upon the models for perfect inspection, algorithms are presented to find the optimal solution. Numerical examples are presented in each Chapter to illustrate how models and algorithms work

Essays on Product Recall Strategies and Effectiveness in the FDA-Regulated Food Sector

This dissertation consists of two complementary essays that investigate current product recall strategies in the Food and Drug Administration (FDA) regulated food sector. These studies address operations and supply chain factors that influence recall effectiveness with two theoretically-based, empirical approaches. The first essay examines recall effectiveness as measured by time to recall, a proxy for potential consumer exposure to hazardous products (Hora, Bapuji and Roth, 2011) using duration analysis techniques. The unit of analysis is a recall event as documented by the product recall press release. Essay 1 addresses the following question: how do supply chain competencies related to integration and monitoring systems between supply chain partners, in addition to supply chain complexity factors, relate to time to recall? The second essay investigates individual consumer perceptions of operational and supply chain information in the context of a product recall announcement. Consumer perceptions of product recalls are important indicators of recall effectiveness since they are linked, theoretically and empirically, with future consumer behavior; and therefore can affect future market share (Siomkos & Kurzbard, 1994). The unit of analysis is the consumer and a behavioral experiment is implemented to capture the effects of salient factors on consumer perceptions. Essay 2 examines the following question: how does information provided regarding operational and supply chain management aspects of product failure affect consumer perceptions and repurchase intent when a product is recalled? The first essay, \u27An Econometric Analysis of Product Recall Strategies and Time to Recall in the Food Industry,\u27 subjects firms\u27 proactive versus reactive product recall strategies to rigorous empirical scrutiny. In addition, we operationalize supply chain recall detection competence (SCRDC), which reflects the combined operational monitoring, integration and coordination systems across supply chain business partners. We use detection entity as a proxy for SCRDC, with the notion that superior SCRDC will be reflected, in part, by recall defects that are detected internally (i.e., by a supplier or the firm conducting the recall) rather than externally (i.e., by a consumer or a regulatory agency). We integrate multiple secondary data sources and apply duration analysis methods to test our model. Time to recall is an important aspect of recall effectiveness, since perishable products have a finite shelf life; consequently, there is a small window of opportunity in which a recall can be conducted in a way that actually reduces consumer exposure. We find that internal detections (i.e., defects detected by a supplier, or the recalling firm, rather than a consumer or a regulatory agency) have a shorter time to recall than external detections. In addition, our proxy for a firm\u27s quality process maturity (i.e., the number of days of production affected by a particular defect) has a direct effect on time to recall (i.e., longer affected production periods are related to a longer time to recall). These findings have significant implications for future research, practice and policy, in part, because they suggest what types of supply chain strategies and governmental regulations might be implemented to reduce time to recall. Essay 1 contributes to operations and supply chain management theory and product recall research by extending quality management theory (Crosby, 1979; Juran, 1992; Roth, Giffi, Seal, 1992) via the notion of SCRDC, integrating notions of supply chain complexity (Bozarth, Warsing, Flynn and Flynn, 2009), and illustrating key differences between the applicability of proactive or reactive recall strategies to food products as compared to durable products (e.g., toys, medical devices, automobiles and other consumer products). The second essay, \u27Consumer Perceptions of Product Recall Strategies: The Effect of Attribution on Repurchase Intent, Recall Satisfaction, and Recall Responsibility,\u27 uses a vignette-based experiment to examine the effects of firm communication to the public regarding the causes of quality failures on consumer perceptions of recall responsibility, recall satisfaction, and repurchase intent. We conduct an exploratory study that manipulates these three dimensions based on attribution theory (i.e., locus, controllability, corrective action) as experimental factors. We find that external locus failures (i.e., defects that happened within a supplier\u27s operations) are related to higher levels of recall satisfaction and a shifting of responsibility away from the recalling firm and towards the supplier. Uncontrollable failures (i.e., failures outside of the volitional control of the recalling firm or supplier) appear to be better tolerated by consumers than controllable failures, as evidenced by effects on repurchase intent, recall satisfaction, and recall responsibility. Finally, providing information about a corrective action intended to address the underlying problem which caused the recall is linked to higher levels of recall satisfaction. Essay 2 contributes to supply chain management theory by adapting attribution theory to the context of operational and supply chain quality failures. In addition to providing preliminary implications for product recall research, this theoretical adaptation may be more broadly applicable to other situations where firms need to communicate to consumers regarding supply chain and operational events, including supply chain disruptions and corporate social responsibility issues. In summary, understanding the effectiveness of recall systems in removing potentially harmful products from the hands of consumers, as well as understanding the consumer perceptions of those systems, is not only important for the creation and maintenance of sustainable supply chain performance, it is important for public health and well-being. In addition, this research suggests potential avenues for policy intervention which could provide additional incentives for firms to improve their quality processes. Future research can determine how these findings may (or may not) be generalizable to other industries and product types