Download Free Software Error Detection Models Book in PDF and EPUB Free Download. You can read online Software Error Detection Models and write the review.

This report describes a continuing research effort in software reliability which was first reported in 'System Test Methodology, ' Naval Postgraduate School, Vol I NPS55SS75072A, Vol. II NPS 55SS75072B (1975). The work just completed involved: improvement of the software error simulation model; validation of the software error simulation model; and analysis of program complexity with simulation and analytical models, using 44 Naval Tactical Data System procedures. The results which were achieved are the following: (1) all validation tests were passed; however simulation results were generally higher than analytical results and (2) the general direction of the relationship between complexity measures and error detection was as expected; however, considerable variability was exhibited when single independent variables were used. It appeared that a multivariable model involving error detection and several program complexity measures would be more appropriate. (Author).
A model of the error detection process for the testing of software has been developed to investigate the relationship between computer program structure and error detection and test effort. The model has been implemented as a simulation.
The objective of this study was to develop a parsimonious model whose parameters have a physical interpretation, and which can be used to predict various quantitative measures for software performance assessment. With this objective, the behavior of the software failure counting process (N(t), t equal to or greater than zero) has been studied. It is shown that N(t) can be well described by a non-homogeneous Poisson process (NHPP) with a two parameter exponentially decaying error detection rate. Several measures, such as the number of failures by some prespecified time, the number of errors remaining in the system at a future time, and software reliability during a mission, have been proposed in this report. Models for software performance assessment are also derived. Two methods are developed to estimate model parameters from either failure count data or times between failures. A goodness-of-fit test is also developed to check the adequacy of the fitted model. Finally, actual failure data are analyzed from two DOD software systems. One is a large command and control system and the other a Naval data analysis system. (Author).
Software Quality Control, Error, Analysis
Software Quality Control, Error, Analysis
This book focuses on software fault detection and correction processes, presenting 5 different paired models introduced over the last decade and discussing their applications, in particular to determining software release time. The first work incorporates the testing effort function and the fault introduction process into the paired fault detection and fault correction models. The second work incorporates fault dependency, while the third adopts a Markov approach for studying fault detection and correction processes. The fourth work considers the multi-release property of various software, and models fault detection and correction processes. The last work classifies faults into four types and models the fault-detection and correction processes. Enabling readers to familiarize themselves with how software reliability can be modeled when different factors need to be considered, and how the approaches can be used to analyze other systems, the book is important reference guide for researchers in the field of software reliability engineering and practitioners working on software projects. To gain the most from the book, readers should have a firm grasp of the fundamentals of the stochastic process.
Software reliability is one of the most important characteristics of software product quality. Its measurement and management technologies during the software product life cycle are essential to produce and maintain quality/reliable software systems. Part 1 of this book introduces several aspects of software reliability modeling and its applications. Hazard rate and nonhomogeneous Poisson process (NHPP) models are investigated particularly for quantitative software reliability assessment. Further, imperfect debugging and software availability models are discussed with reference to incorporating practical factors of dynamic software behavior. Three software management problems are presented as application technologies of software reliability models: the optimal software release problem, the statistical testing-progress control, and the optimal testing-effort allocation problem. Part 2 of the book describes several recent developments in software reliability modeling and their applications as quantitative techniques for software quality/reliability measurement and assessment. The discussion includes a quality engineering analysis of human factors affecting software reliability during the design review phase, which is the upper stream of software development, as well as software reliability growth models based on stochastic differential equations and discrete calculus during the testing phase, which is the lower stream. The final part of the book provides an illustration of quality-oriented software management analysis by applying the multivariate analysis method and the existing software reliability growth models to actual process monitoring data.
This book presents the basic concepts of software reliability growth models (SRGMs), ranging from fundamental to advanced level. It discusses SRGM based on the non-homogeneous Poisson process (NHPP), which has been a quite successful tool in practical software reliability engineering. These models consider the debugging process as a counting process characterized by its mean value function. Model parameters have been estimated by using either the maximum likelihood method or regression. NHPP SRGMs based on inverse Weibull, generalized inverse Weibull, extended inverse Weibull, generalized extended inverse Weibull, and delayed S-shaped have been focused upon. Review of literature on SRGM has been included from the scratch to recent developments, applicable in artificial neural networks, machine learning, artificial intelligence, data-driven approaches, fault-detection, fault-correction processes, and also in random environmental conditions. This book is designed for practitioners and researchers at all levels of competency, and also targets groups who need information on software reliability engineering.