Testing effort dependent software reliability model for imperfect debugging process considering both detection and correction

This paper studies the fault detection process (FDP) and fault correction process (FCP) with the incorporation of testing effort function and imperfect debugging. In order to ensure high reliability, it is essential for software to undergo a testing phase, during which faults can be detected and corrected by debuggers. The testing resource allocation during this phase, which is usually depicted by the testing effort function, considerably influences not only the fault detection rate but also the time to correct a detected fault. In addition, testing is usually far from perfect such that new faults may be introduced. In this paper, we first show how to incorporate testing effort function and fault introduction into FDP and then develop FCP as delayed FDP with a correction effort. Various specific paired FDP and FCP models are obtained based on different assumptions of fault introduction and correction effort. An illustrative example is presented. The optimal release policy under different criteria is also discussed

Entropy based Software Reliability Growth Modelling for Open Source Software Evolution

During Open Source Software (OSS) development, users submit "new features (NFs)", "feature improvements (IMPs)" and bugs to fix. A proportion of these issues get fixed before the next software release. During the introduction of NFs and IMPs, the source code files change. A proportion of these source code changes may result in generation of bugs. We have developed calendar time and entropy-dependent mathematical models to represent the growth of OSS based on the rate at which NFs are added, IMPs are added, and bugs introduction rate.The empirical validation has been conducted on five products, namely "Avro, Pig, Hive, jUDDI and Whirr" of the Apache open source project. We compared the proposed models with eminent reliability growth models, Goel and Okumoto (1979) and Yamada et al. (1983) and found that the proposed models exhibit better goodness of fit

Multiple IMU system development, volume 1

A redundant gimballed inertial system is described. System requirements and mechanization methods are defined and hardware and software development is described. Failure detection and isolation algorithms are presented and technology achievements described. Application of the system as a test tool for shuttle avionics concepts is outlined

Design de fiabilidade bidimensional do software de múltiplos lançamentos tendo em conta o fator de redução de falhas na depuração imperfeita

Introduction: The present research was conducted at the University of Delhi, India in 2017. Methods: We develop a software reliability growth model to assess the reliability of software products released in multiple versions under limited availability of resources and time. The Fault Reduction Factor (frf) is considered to be constant in imperfect debugging environments while the rate of fault removal is given by Delayed S-Shaped model. Results: The proposed model has been validated on a real life four-release dataset by carrying out goodness of fit analysis. Laplace trend analysis was also conducted to judge the trend exhibited by data with respect to change in the system’s reliability. Conclusions: A number of comparison criteria have been calculated to evaluate the performance of the proposed model relative to only time-based multi-release Software Reliability Growth Model (srgm). Originality: In general, the number of faults removed is not the same as the number of failures experienced in given time intervals, so the inclusion of frf in the model makes it better and more realistic. A paradigm shift has been observed in software development from single release to multi release platform. Limitations: The proposed model can be used by software developers to take decisions regarding the release time for different versions, by either minimizing the development cost or maximizing the reliability and determining the warranty policies.Introducción: la presente investigación se realizó en la Universidad de Delhi, India en 2017. Métodos: desarrollamos un modelo de crecimiento de confiabilidad de software para evaluar la confiabilidad de los productos de software lanzados en múltiples versiones bajo disponibilidad limitada de recursos y tiempo. El factor de reducción de fallas (frf) se considera una constante en entornos de depuración imperfecta, mientras que la tasa de eliminación de fallas está dada por el modelo de forma retardada en S. Resultados: se valida el modelo propuesto en un conjunto de datos de cuatro lanzamientos de la vida real mediante un análisis de bondad de ajuste. También se aplicó el análisis de tendencia de Laplace para juzgar la tendencia que presentan los datos con respecto al cambio en la confiabilidad del sistema. Conclusiones: se calculó una serie de criterios de comparación para evaluar el rendimiento del modelo propuesto en relación con el modelo de crecimiento de confiabilidad del software (srgm) de múltiples lanzamientos basado únicamente en el tiempo. Originalidad: en general, el número de fallas eliminadas no es el mismo que el número de fallas experimentadas en intervalos de tiempo determinados, por lo que la inclusión de frf en el modelo lo mejora y lo hace más realista. Se ha observado un cambio de paradigma en el desarrollo de software, que pasa de un lanzamiento único a una plataforma múltiples lanzamientos. Limitaciones: los desarrolladores de software pueden emplear el modelo propuesto para tomar decisiones con respecto al tiempo de lanzar diferentes versiones, ya sea minimizando el costo de desarrollo o maximizando la confiabilidad y determinando las políticas de la garantía.Introdução: esta pesquisa foi realizada na Universidade de Deli, na Índia, em 2017. Métodos: desenvolvemos um modelo de crescimento de confiabilidade de software para avaliar a confiabilidade dos produtos de software lançados em múltiplas versões sob disponibilidade limitada de recursos e tempo. O fator de redução de falhas (frf) é considerado uma constante em contextos de depuração imperfeita, enquanto a taxa de eliminação de falhas é dada pelo modelo de forma retardada em S.Resultados: o modelo proposto é avaliado em um conjunto de dados de quatro lançamentos da vida real mediante uma análise de bondade de ajuste. Também foi utilizada a análise de tendência de Laplace para avaliar a tendência apresentada pelos dados com respeito à mudança na confiabilidade do sistema.Conclusões: uma série de critérios de comparação foi calculada para avaliar o rendimento do modelo proposto em relação com o modelo de crescimento de confiabilidade do software (srgm) de múltiplos lançamentos baseado unicamente no tempo.Originalidade: em geral, o número de falhas eliminadas não é o mesmo que o número de falhas existentes em intervalos de tempo determinados, sendo assim, a inclusão do frf no modelo o torna melhor e mais realista. Foi observada uma mudança de paradigma no desenvolvimento de software, que passa de um lançamento único a uma plataforma de múltiplos lançamentos.Limitações: o modelo proposto pode ser utilizado pelos desenvolvedores de software para tomar decisões com respeito ao tempo de lançar diferentes versões, seja para minimizar o custo de desenvolvimento ou maximizar a confiabilidade e determinar as políticas de garantia

Meeting the design challenges of nano-CMOS electronics: an introduction to an upcoming EPSRC pilot project

The years of ‘happy scaling’ are over and the fundamental challenges that the semiconductor industry faces, at both technology and device level, will impinge deeply upon the design of future integrated circuits and systems. This paper provides an introduction to these challenges and gives an overview of the Grid infrastructure that will be developed as part of a recently funded EPSRC pilot project to address them, and we hope, which will revolutionise the electronics design industry

Critical Fault-Detecting Time Evaluation in Software with Discrete Compound Poisson Models

Software developers predict their product’s failure rate using reliability growth models that are typically based on nonhomogeneous Poisson (NHP) processes. In this article, we extend that practice to a nonhomogeneous discrete-compound Poisson process that allows for multiple faults of a system at the same time point. Along with traditional reliability metrics such as average number of failures in a time interval, we propose an alternative reliability index called critical fault-detecting time in order to provide more information for software managers making software quality evaluation and critical market policy decisions. We illustrate the significant potential for improved analysis using wireless failure data as well as simulated data

Software reliability modeling and analysis

Ph.DDOCTOR OF PHILOSOPH

Fault detection and correction modeling of software systems

Ph.DDOCTOR OF PHILOSOPH

Energy-efficient wireless communication

In this chapter we present an energy-efficient highly adaptive network interface architecture and a novel data link layer protocol for wireless networks that provides Quality of Service (QoS) support for diverse traffic types. Due to the dynamic nature of wireless networks, adaptations in bandwidth scheduling and error control are necessary to achieve energy efficiency and an acceptable quality of service. In our approach we apply adaptability through all layers of the protocol stack, and provide feedback to the applications. In this way the applications can adapt the data streams, and the network protocols can adapt the communication parameters