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Software Quality Control, Error, Analysis
Software Quality Control, Error, Analysis
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.
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Errors are information. In contrastive linguistics, they are thought to be caused by unconscious transfer of mother tongue structures to the system of the target language and give information about both systems. In the interlanguage hypothesis of second language acquisition, errors are indicative of the different intermediate learning levels and are useful pedagogical feedback. In both cases error analysis is an essential methodological tool for diagnosis and evaluation of the language acquisition process. Errors, too, give information in psychoanalysis (e.g., the Freudian slip), in language universal research, and in other fields of linguistics, such as linguistic change.This bibliography is intended to stimulate study into cross-language, cross-discipline and cross-theoretical, as well as for language universal, use of the numerous, but sometimes hard to come by, error analysis studies. 5398 titles covering the period 1578 up to 1990 (with work in more than 144 languages and language families) are cited, cross-referenced, and described. The subject areas covered are numerous. For example: Theoretical Linguistics (Linguistic Typology, Cognitive Linguistics), Historical Linguistics (Language Change), Applied Linguistics (e.g. Speech Disorders), Translation, Mother Tongue Acquisition, Foreign Language Learning (Negative Transfer, Intralingual and Interlingual Errors), Psychoanalysis (Slips of the Tongue), Typography, Shorthand, Clinical Linguistics and Speech Pathology, Reading Research, Automatic Error Detection, Contact Linguistics (Code-switching, Interference), etc.
In software engineering, it is easy to propose techniques for improving software development but difficult to test the claims made for such techniques. This report suggests an error analysis technique for use in gathering data concerning the effectiveness of different software development methodologies. The principal features of the error analysis technique described are formulating questions of interest and a data classification scheme before collection begins, and interviewing of system developers concomitant with the development process to verify the accuracy of the data. The data obtained by using this technique during the development of a medium-size software development project are presented. This project was known as the Architecture Research Facility (ARF) and took about 10 months and 192 man-weeks of effort to develop. The ARF designers used the information-hiding principle to modularize the system, and interface specifications and high-level language coding specifications to express the design. Several error-detection aids were designed into the system to help detect run-time errors. In addition, quality control rules were established that required specification review before coding, and code review after compilation but prior to testing. A total of 143 errors was reported. Analysis of these errors showed that there were few problems caused by intermodule interfaces, that error corrections rarely required knowledge of more than one module, that most errors took less than a few hours to fix, and that error-detection aids detected more than half the errors that were potentially detectable by them. (Author).
All students taking laboratory courses within the physical sciences and engineering will benefit from this book, whilst researchers will find it an invaluable reference. This concise, practical guide brings the reader up-to-speed on the proper handling and presentation of scientific data and its inaccuracies. It covers all the vital topics with practical guidelines, computer programs (in Python), and recipes for handling experimental errors and reporting experimental data. In addition to the essentials, it also provides further background material for advanced readers who want to understand how the methods work. Plenty of examples, exercises and solutions are provided to aid and test understanding, whilst useful data, tables and formulas are compiled in a handy section for easy reference.
This book reviews existing operational software failure analysis techniques and proposes near-miss analysis as a novel, and new technique for investigating and preventing software failures. The authors provide details on how near-miss analysis techniques focus on the time-window before the software failure actually unfolds, so as to detect the high-risk conditions that can lead to a major failure. They detail how by alerting system users of an upcoming software failure, the detection of near misses provides an opportunity to collect at runtime failure-related data that is complete and relevant. They present a near-miss management systems (NMS) for detecting upcoming software failures, which can contribute significantly to the improvement of the accuracy of the software failure analysis. A prototype of the NMS is implemented and is discussed in the book. The authors give a practical hands-on approach towards doing software failure investigations by means of near-miss analysis that is of use to industry and academia