An in-depth review of key techniques in software error detection Software error detection is one of the most challenging problems in software engineering. Now, you can learn how to make the most of software testing by selecting test cases to maximize the probability of revealing latent errors. Software Error Detection through Testing and Analysis begins with a thorough discussion of test-case selection and a review of the concepts, notations, and principles used in the book. Next, it covers: Code-based test-case selection methods Specification-based test-case selection methods Additional advanced topics in testing Analysis of symbolic trace Static analysis Program instrumentation Each chapter begins with a clear introduction and ends with exercises for readers to test their understanding of the material. Plus, appendices provide a logico-mathematical background, glossary, and questions for self-assessment. Assuming a basic background in software quality assurance and an ability to write nontrivial programs, the book is free of programming languages and paradigms used to construct the program under test. Software Error Detection through Testing and Analysis is suitable as a professional reference for software testing specialists, software engineers, software developers, and software programmers. It is also appropriate as a textbook for software engineering, software testing, and software quality assurance courses at the advanced undergraduate and graduate levels.

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.

Since 1995, when the SPIN workshop series was instigated, SPIN workshops have been held on an annual basis in Montr ́ eal (1995), New Brunswick (1996), Enschede (1997), Paris (1998), Trento (1999), Toulouse (1999), Stanford (2000), Toronto (2001), Grenoble (2002) and Portland (2003). All but the ?rst SPIN workshop were organized as satellite events of larger conferences, in particular of CAV (1996), TACAS (1997), FORTE/PSTV (1998), FLOC (1999), the World Congress on Formal Methods (1999), FMOODS (2000), ICSE (2001, 2003) and ETAPS (2002). This year again, SPIN was held as a satellite event of ETAPS 2004. The co-location of SPIN workshops with conferences has proven to be very successful and has helped to disseminate SPIN model checking technology to wider audiences. Since 1999, the proceedings of the SPIN workshops have appeared in Springer-Verlag’s Lecture Notes in Computer Science series. The history of successful SPIN workshops is evidence for the maturing of model checking technology, not only in the hardware domain, but increasingly also in the software area. While in earlier years algorithms and tool development aroundtheSPINmodelcheckerwerethefocusofthisworkshopseries,forseveral years now the scope has been widened to include more general approaches to software model checking techniques and tools as well as applications. The SPIN workshop has become a forum for all practitioners and researchers interested in model checking based techniques for the validation and analysis of communication protocols and software systems.

Software Quality Control, Error, Analysis

also in: THE KLUWER INTERNATIONAL SERIES ON ASIAN STUDIES IN COMPUTER AND INFORMATION SCIENCE, Volume 1