Details

Analytic Methods in Systems and Software Testing


Analytic Methods in Systems and Software Testing


1. Aufl.

von: Ron S. Kenett, Fabrizio Ruggeri, Frederick W. Faltin

64,99 €

Verlag: Wiley
Format: PDF
Veröffentl.: 20.06.2018
ISBN/EAN: 9781119487364
Sprache: englisch
Anzahl Seiten: 568

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Beschreibungen

A comprehensive treatment of systems and software testing using state of the art methods and tools This book provides valuable insights into state of the art software testing methods and explains, with examples, the statistical and analytic methods used in this field. Numerous examples are used to provide understanding in applying these methods to real-world problems. Leading authorities in applied statistics, computer science, and software engineering present state-of-the-art methods addressing challenges faced by practitioners and researchers involved in system and software testing. Methods include: machine learning, Bayesian methods, graphical models, experimental design, generalized regression, and reliability modeling. Analytic Methods in Systems and Software Testing presents its comprehensive collection of methods in four parts: Part I: Testing Concepts and Methods; Part II: Statistical Models; Part III: Testing Infrastructures; and Part IV: Testing Applications. It seeks to maintain a focus on analytic methods, while at the same time offering a contextual landscape of modern engineering, in order to introduce related statistical and probabilistic models used in this domain. This makes the book an incredibly useful tool, offering interesting insights on challenges in the field for researchers and practitioners alike. Compiles cutting-edge methods and examples of analytical approaches to systems and software testing from leading authorities in applied statistics, computer science, and software engineering Combines methods and examples focused on the analytic aspects of systems and software testing Covers logistic regression, machine learning, Bayesian methods, graphical models, experimental design, generalized regression, and reliability models Written by leading researchers and practitioners in the field, from diverse backgrounds including research, business, government, and consulting Stimulates research at the theoretical and practical level  Analytic Methods in Systems and Software Testing is an excellent advanced reference directed toward industrial and academic readers whose work in systems and software development approaches or surpasses existing frontiers of testing and validation procedures. It will also be valuable to post-graduate students in computer science and mathematics.
List of Contributors Preface Part I: Testing Concepts and Methods 1 Recent Advances in Classifying Risk-Based Testing ApproachesMichael Felderer, Jürgen Großmann, and Ina Schieferdecker 2 Improving Software Testing with Causal Modeling Norman Fenton and Martin Neil 3 Optimal Software Testing across Version ReleasesSimon P. Wilson and Seán Ó Ríordáin 4 Incremental Verification and Coverage Analysis of Strongly Distributed SystemsElena V. Ravve and Zeev Volkovich 5 Combinatorial Testing: An Approach to Systems and Software Testing Based on Covering ArraysJoseph Morgan 6 Conceptual Aspects in Development and Teaching of System and Software Test EngineeringDani Almog, Ron S. Kenett, Uri Shafrir, and Hadas Chasidim Part II: Statistical Models 7 Non-homogeneous Poisson Process Models for Software ReliabilitySteven E. Rigdon 8 Bayesian Graphical Models for High Complexity Testing: Aspects of ImplementationDavid Wooff, Michael Goldstein, and Frank Coolen 9 Models of Software ReliabilityShelemyahu Zacks 10 Improved Estimation of System Reliability with Application in Software DevelopmentBeidi Qiang and Edsel A. Peña 11 Decision Models for Software TestingFabrizio Ruggeri and Refik Soyer 12 Modeling and Simulations in Control Software DesignJiri Koziorek, Stepan Ozana, Vilem Srovnal, and Tomas Docekal Part III: Testing Infrastructures 13 A Temperature Monitoring Infrastructure and Process for Improving Data Center Energy Efficiency with Results for an HPC Data CenterSarah E. Michalak, Amanda M. Bonnie, Andrew J. Montoya, Curtis B. Storlie, William N. Rust, Lawrence O. Ticknor, Laura A. Davey, Thomas E. Moxley III, and Brian J. Reich 14 Agile Testing with User Data in Cloud and Edge Computing EnvironmentsRon S. Kenett, Avi Harel, and Fabrizio Ruggeri 15 Automated Software TestingXiaoxu Diao, Manuel Rodriguez, Boyuan Li, and Carol Smidts 16 Dynamic Test Case Selection in Continuous Integration: Test Result Analysis using the Eiffel FrameworkDaniel Ståhl and Jan Bosch 17 An Automated Regression Testing Framework for a Hadoop-Based Entity Resolution SystemDaniel Pullen, Pei Wang, Joshua R. Johnson, and John R. Talburt Part IV: Testing Applications 18 Testing Defense SystemsLaura J. Freeman, Thomas Johnson, Matthew Avery, V. Bram Lillard, and Justace Clutter 19 A Search-Based Approach to Geographical Data Generation for Testing Location-Based ServicesXiaoying Bai, Kejia Hou, Jun Huang, and Mingli Yu 20 Analytics in Testing Communication SystemsGilli Shama 21 Measures in Systems Integration Verification and Validation Phase and Aerospace Applications Field ExperienceSarit Assaraf and Ron S. Kenett Index
Ron S. Kenett is Chairman of KPA Ltd and Senior Research Fellow at the Samuel Neaman Institute, Technion, Israel. Fabrizio Ruggeri is Research Director at CNR IMATI, Milano, Italy. Frederick W. Faltin is Co-Founder of The Faltin Group, Cody, WY, and Associate Professor of Practice, Department of Statistics, Virginia Tech, Blacksburg, VA, USA.
A comprehensive treatment of systems and software testing using state of the art methods and tools This book provides valuable insights into state of the art software testing methods and explains, with examples, the statistical and analytic methods used in this field. Numerous examples are used to provide understanding in applying these methods to real-world problems. Leading authorities in applied statistics, computer science, and software engineering present state-of-the-art methods addressing challenges faced by practitioners and researchers involved in system and software testing. Methods include: machine learning, Bayesian methods, graphical models, experimental design, generalized regression, and reliability modeling. Analytic Methods in Systems and Software Testing presents its comprehensive collection of methods in four parts: Part I: Testing Concepts and Methods; Part II: Statistical Models; Part III: Testing Infrastructures; and Part IV: Testing Applications. It seeks to maintain a focus on analytic methods, while at the same time offering a contextual landscape of modern engineering, in order to introduce related statistical and probabilistic models used in this domain. This makes the book an incredibly useful tool, offering interesting insights on challenges in the field for researchers and practitioners alike. Compiles cutting-edge methods and examples of analytical approaches to systems and software testing from leading authorities in applied statistics, computer science, and software engineering Combines methods and examples focused on the analytic aspects of systems and software testing Covers logistic regression, machine learning, Bayesian methods, graphical models, experimental design, generalized regression, and reliability models Written by leading researchers and practitioners in the field, from diverse backgrounds including research, business, government, and consulting Stimulates research at the theoretical and practical level  Analytic Methods in Systems and Software Testing is an excellent advanced reference directed toward industrial and academic readers whose work in systems and software development approaches or surpasses existing frontiers of testing and validation procedures. It will also be valuable to post-graduate students in computer science and mathematics.

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