The Domain Testing Workbook

The Domain Testing Workbook

Cem Kaner

Language: English

Pages: 488

ISBN: 0989811905

Format: PDF / Kindle (mobi) / ePub


Domain testing is the most widely taught technique in software testing. However, many of the presentations stick with examples that are too simple to provide a strong basis for applying the technique. Others focus on mathematical models or analysis of the program’s source code. The Domain Testing Workbook will help you develop deep skill with this technique whether or not you have access to source code or an abiding interest in mathematics.

The Domain Testing Workbook provides a schema to organize domain testing and test design, with dozens of practical problems and sample analyses. Readers can try their hand at applying the schema and compare their analyses against over 200 pages of worked examples.

You will learn:

  • when and how to use domain testing;
  • how to apply a risk-focused approach with domain testing;
  • how to use domain testing within a broader testing strategy; and
  • how to use domain testing in an exploratory way.

This book is for:

  • Software testers who want to develop expertise in the field’s most popular test technique
  • Test managers who want to assess and improve their staff’s skills
  • Trainers and professors interested in adding depth and skill-based learning to black box testing or test design classes.

Cem Kaner, J.D., Ph.D., is Professor of Software Engineering at the Florida Institute of Technology. Dr. Kaner is senior author of Testing Computer Software, Lessons Learned in Software Testing and Bad Software. The ACM’s Special Interest Group for Computers and Society presented him with the Making a Difference Award in 2009 and the Software Test Professionals presented him with the Software Test Luminary Award in 2012. Kaner was a founder of the Association for Software Testing. He is lead developer of the BBST™ (Black Box Software Testing) courses and courseware.

Sowmya Padmanabhan, M.Sc., currently works at Google as a Program Manager. Before that she worked in Program Management and Software Development/Test at Microsoft and at Texas Instruments. She has a Masters degree in Computer Sciences with a specialization in Software Testing. Sowmya’s thesis involved extensive research in training new testers to do skilled Domain Testing.

Douglas Hoffman, M.S.E.E., M.B.A, is an independent management consultant with Software Quality Methods, LLC. He is a Fellow of the American Society for Quality. He has authored numerous papers and is a contributing author of Experiences of Test Automation. He has taught several courses on software testing and test automation for the University of California’s Extension campuses. He has served as President of the Association for Software Testing and of the Silicon Valley Software Quality Association and as Section Chair of the Silicon Valley Section of ASQ.

Working With Unix Processes

Practical Analysis of Algorithms (Undergraduate Topics in Computer Science)

 

 

 

 

 

 

 

 

 

 

 

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standard library functions in most modern compiled programming languages will prevent most of these problems. • Some of the bugs, such as buffer overflows, seem to still not be well-controlled. • Other bugs seem to be mostly gone, but you might still see colonies of them in: º Programs written in custom-designed languages. º Some code written in some of the scripted languages. º Code that has been heavily speed-optimized and space-optimized to control specialized devices.49 º Code written

one dimension, but to test the values of any dimension, you must specify values for all of the others. We have to cover a few items that are common to the next few chapters, primarily some core terminology, notation and a few design concepts before proceeding to the Chapters: • An overview of three design traditions that underlie multivariable testing • Notation for multidimensional variables (N-tuple notation) • The combinatorial explosion • An overview of the four basic questions in the

available in memory for any number larger than MAXINT. If you somehow store a larger number for K, you achieve an “overflow” and corrupt part of memory that is not allocated to storing a value for K. That would be a serious error. • The absolutely biggest value we can imagine trying to store in K is MAXINT × MAXINT (I and J both MAXINT). For a variable whose possible values are so tightly constrained, we recommend using the simpler domain analysis table. This table shows what values of K are

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