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

A Study of Equivalent and Stubborn Mutation Operators using Human Analysis of Equivalence

Though mutation testing has been widely studied for more than thirty years, the prevalence and properties of equivalent mutants remain largely unknown. We report on the causes and prevalence of equivalent mutants and their relationship to stubborn mutants (those that remain undetected by a high quality test suite, yet are non-equivalent). Our results, based on manual analysis of 1,230 mutants from 18 programs, reveal a highly uneven distribution of equivalence and stubbornness. For example, the ABS class and half UOI class generate many equivalent and almost no stubborn mutants, while the LCR class generates many stubborn and few equivalent mutants. We conclude that previous test effectiveness studies based on fault seeding could be skewed, while developers of mutation testing tools should prioritise those operators that we found generate disproportionately many stubborn (and few equivalent) mutants

Reliability Analysis of Component-Based Systems with Multiple Failure Modes

This paper presents a novel approach to the reliability modeling and analysis of a component-based system that allows dealing with multiple failure modes and studying the error propagation among components. The proposed model permits to specify the components attitude to produce, propagate, transform or mask different failure modes. These component-level reliability specifications together with information about systems global structure allow precise estimation of reliability properties by means of analytical closed formulas, probabilistic modelchecking or simulation methods. To support the rapid identification of components that could heavily affect systems reliability, we also show how our modeling approach easily support the automated estimation of the system sensitivity to variations in the reliability properties of its components. The results of this analysis allow system designers and developers to identify critical components where it is worth spending additional improvement efforts

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

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