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.

Software Quality Control, Error, Analysis

Software Quality Control, Error, Analysis

The purpose of the paper is to describe a model for statistically analyzing software error detection and correction processes during software functional testing. The purpose of the model is to provide decision aids for controlling the quality of command and control system software. The inputs to the model are error detection histories and the outputs are forecasts of the future behavior of error detection and correction processes. The model outputs would provide software production and quality control management with quantitative guidelines for establishing testing strategies, making the acceptance/rejection decision, and evaluating the tradeoff between incremental quality improvement and incremental resource investment.

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).