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.

Autorentext

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.

Klappentext
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. This book:

• 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.

Inhalt
List of Contributors ix

Preface xv

Part I Testing Concepts andMethods 1

1 Recent Advances in Classifying Risk-Based Testing Approaches 3
Michael Felderer, Jürgen Großmann, and Ina Schieferdecker

2 Improving Software Testing with Causal Modeling 27
Norman Fenton andMartin Neil

3 Optimal Software Testing across Version Releases 65
Simon P.Wilson and Seán Ó Ríordáin

4 Incremental Verification and Coverage Analysis of Strongly Distributed Systems 81
Elena V. Ravve and Zeev Volkovich

5 Combinatorial Testing: An Approach to Systems and Software Testing Based on Covering Arrays 131
Joseph Morgan

6 Conceptual Aspects in Development and Teaching of Systemand Software Test Engineering 159
Dani Almog, Ron S. Kenett, Uri Shafrir, and Hadas Chasidim

Part II Statistical Models 195

7 Non-homogeneous Poisson Process Models for Software Reliability 197
Steven E. Rigdon

8 Bayesian Graphical Models for High-Complexity Testing: Aspects of Implementation 213
DavidWooff,Michael Goldstein, and Frank Coolen

9 Models of Software Reliability 245
Shelemyahu Zacks

10 Improved Estimation of SystemReliability with Application in Software Development 255
Beidi Qiang and Edsel A. Peña

11 Decision Models for Software Testing 277
Fabrizio Ruggeri and Refik Soyer

12 Modeling and Simulations in Control Software Design 287
Jiri Koziorek, Stepan Ozana, Vilem Srovnal, and Tomas Docekal

Part III Testing Infrastructures 327

13 A Temperature Monitoring Infrastructure and Process for Improving Data Center Energy Efficiency with Results for a High Performance Computing Data Center 329
Sarah E.Michalak, AmandaM. 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 Environments 353
Ron S. Kenett, Avi Harel, and Fabrizio Ruggeri

15 Automated Software Testing 373
Xiaoxu Diao,Manuel Rodriguez, Boyuan Li, and Carol Smidts

16 Dynamic Test Case Selection in Continuous Integration: Test Result Analysis using the Eiffel Framework 405
Daniel Ståhl and Jan Bosch

17 An Automated Regression Testing Framework for a Hadoop-Based Entity Resolution System 415
Daniel Pullen, PeiWang, Joshua R. Johnson, and John R. Talburt

Part IV Testing Applications 439

18 Testing Defense Systems 441
Laura 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 Services 489
Xiaoying Bai, Kejia Hou, Jun Huang, andMingli Yu

20 Analytics in Testing Communication Systems 501
Gilli Shama

21 Measures in the Systems Integration Verification and Validatio…