Acceptance Criteria for Critical Software Based on Testability Estimates and Test Results

Testability is defined as the probability that a program will fail a test, conditional on the program containing some fault. In this paper, we show that statements about the testability of a program can be more simply described in terms of assumptions on the probability distribution of the failure intensity of the program. We can thus state general acceptance conditions in clear mathematical terms using Bayesian inference. We develop two scenarios, one for software for which the reliability requirements are that the software must be completely fault-free, and another for requirements stated as an upper bound on the acceptable failure probability

Software fault-freeness and reliability predictions

Many software development practices aim at ensuring that software is correct, or fault-free. In safety critical applications, requirements are in terms of probabilities of certain behaviours, e.g. as associated to the Safety Integrity Levels of IEC 61508. The two forms of reasoning - about evidence of correctness and about probabilities of certain failures -are rarely brought together explicitly. The desirability of using claims of correctness has been argued by many authors, but not been taken up in practice. We address how to combine evidence concerning probability of failure together with evidence pertaining to likelihood of fault-freeness, in a Bayesian framework. We present novel results to make this approach practical, by guaranteeing reliability predictions that are conservative (err on the side of pessimism), despite the difficulty of stating prior probability distributions for reliability parameters. This approach seems suitable for practical application to assessment of certain classes of safety critical systems

The Artificial Society Analytics Platform

Author's accepted manuscriptSocial simulation routinely involves the construction of artificial societies and agents within such societies. Currently there is insufficient discussion of best practices regarding the construction process. This chapter introduces the artificial society analytics platform (ASAP) as a way to spark discussion of best practices. ASAP is designed to be an extensible architecture capable of functioning as the core of many different types of inquiries into social dynamics. Here we describe ASAP, focusing on design decisions in several key areas, thereby exposing our assumptions and reasoning to critical scrutiny, hoping for discussion that can advance debate over best practices in artificial society construction. The five design decisions are related to agent characteristics, neighborhood interactions, evaluating agent credibility, agent marriage, and heritability of personality.acceptedVersio

Traceability for Mutation Analysis in Model Transformation

International audienceModel transformation can't be directly tested using program techniques. Those have to be adapted to model characteristics. In this paper we focus on one test technique: mutation analysis. This technique aims to qualify a test data set by analyzing the execution results of intentionally faulty program versions. If the degree of qualification is not satisfactory, the test data set has to be improved. In the context of model, this step is currently relatively fastidious and manually performed. We propose an approach based on traceability mechanisms in order to ease the test model set improvement in the mutation analysis process. We illustrate with a benchmark the quick automatic identification of the input model to change. A new model is then created in order to raise the quality of the test data set

Comparing Static and Dynamic Weighted Software Coupling Metrics

Coupling metrics that count the number of inter-module connections in a software system are an established way to measure internal software quality with respect to modularity. In addition to static metrics, which are obtained from the source or compiled code of a program, dynamic metrics use runtime data gathered, e.g., by monitoring a system in production. Dynamic metrics have been used to improve the accuracy of static metrics for object-oriented software. We study weighted dynamic coupling that takes into account how often a connection (e.g., a method call) is executed during a system’s run. We investigate the correlation between dynamic weighted metrics and their static counterparts. To compare the different metrics, we use data collected from four different experiments, each monitoring production use of a commercial software system over a period of four weeks. We observe an unexpected level of correlation between the static and the weighted dynamic case as well as revealing differences between class- and package-level analyses

Using Administrative Data to Count and Classify Households with Local Applications

Households rather than individuals are being increasingly used for research and to target and evaluate public policy. As a result accurate and timely household level statistics have become an increasing necessity especially at local level. However, official sources of information on households are fragmented with significant gaps and inaccuracies that limit their usefulness. This paper reviews present statistical arrangements and then describes a new approach to data collection and household classification which combine various local administrative sources. An intermediate step is the creation of local population counts which are converted into household types and these methods are described in two companion papers previously published in this journal. The utility and advantages of the approach are demonstrated using the example of the six Olympic London Boroughs for whom the data collection was undertaken in 2011 and the analysis subsequently

Primordialists and Constructionists: a typology of theories of religion

This article adopts categories from nationalism theory to classify theories of religion. Primordialist explanations are grounded in evolutionary psychology and emphasize the innate human demand for religion. Primordialists predict that religion does not decline in the modern era but will endure in perpetuity. Constructionist theories argue that religious demand is a human construct. Modernity initially energizes religion, but subsequently undermines it. Unpacking these ideal types is necessary in order to describe actual theorists of religion. Three distinctions within primordialism and constructionism are relevant. Namely those distinguishing: a) materialist from symbolist forms of constructionism; b) theories of origins from those pertaining to the reproduction of religion; and c) within reproduction, between theories of religious persistence and secularization. This typology helps to make sense of theories of religion by classifying them on the basis of their causal mechanisms, chronology and effects. In so doing, it opens up new sightlines for theory and research

Starfire Optical Range 3.5-m telescope adaptive optical system

A 941 channel, 1500 Hertz frame rate adaptive optical (AO) system has been installed and tested in the coude path of the 3.5m telescope at the USAF Research Laboratory Starfire Optical Range. This paper describes the design and measured performance of the principal components comprising this system and present sample results from the first closed-loop test of the system on stars and an artificial source simulator