Identifying Relevant Information for Testing Technique Selection

1. Front Matter

   Pages i-xxiii

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2. Introduction

   • Sira Vegas, Natalia Juristo, Victor R. Basili

   Pages 1-10

3. State of the Practice

   • Sira Vegas, Natalia Juristo, Victor R. Basili

   Pages 11-36

4. Research Goals

   • Sira Vegas, Natalia Juristo, Victor R. Basili

   Pages 37-48

5. Problem Solving Process

   • Sira Vegas, Natalia Juristo, Victor R. Basili

   Pages 49-64

6. First Generative Iteration: Deductive Theoretical Schema

   • Sira Vegas, Natalia Juristo, Victor R. Basili

   Pages 65-96

7. Second Generative Iteration: Inductive Empirical Schema

   • Sira Vegas, Natalia Juristo, Victor R. Basili

   Pages 97-134

8. Synthesis of Perspectives: Proposal of the Preliminary Schema

   • Sira Vegas, Natalia Juristo, Victor R. Basili

   Pages 135-145

9. Improvement of the Schema: Expert Peer Review

   • Sira Vegas, Natalia Juristo, Victor R. Basili

   Pages 147-166

10. Empirical Evaluation

    • Sira Vegas, Natalia Juristo, Victor R. Basili

    Pages 167-176

11. Experimental Evaluation

    • Sira Vegas, Natalia Juristo, Victor R. Basili

    Pages 177-240

12. Conclusions

    • Sira Vegas, Natalia Juristo, Victor R. Basili

    Pages 241-243

13. Back Matter

    Pages 245-281

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Engineering tasks are supposed to achieve defined goals under certain project constraints. Example goals of software engineering tasks include achieving a certain functionality together with some level of reliability or performance. Example constraints of software engineering tasks include budget and time limitations or experience limitations of the developers at hand. Planning of an engineering project requires the selection of techniques, methods and tools suited to achieve stated goals under given project constraints. This assumes sufficient knowledge regarding the process-product relationships (or effects) of candidate techniques, methods and tools. Planning of software projects suffers greatly from lack of knowledge regarding the process-product relationships of candidate techniques, methods and tools. Especially in the area of testing a project planner is confronted with an abundance of testing techniques, but very little knowledge regarding their effects under varying project conditions. This book offers a novel approach to addressing this problem: First, based on a comprehensive initial characterization scheme (see chapter 7) an overview of existing testing techniques and their effects under varying conditions is provided to guide the selection of testing approaches. Second, the optimisation of this knowledge base is suggested based on experience from experts, real projects and scientific experiments (chapters 8, 9, and 10). This book is of equal interest to practitioners, researchers and students. Practitioners interested in identifying ways to organize their company-specific knowledge about testing could start with the schema provided in this book, and optimise it further by applying similar strategies as offered in chapters 8 and 9.

• Attribut
• computer
• computer science
• design
• organization
• research methods
• selection
• software
• software engineering
• testing

• Universidad Politecnica de Madrid, Madrid, Spain

  Sira Vegas, Natalia Juristo

• University of Maryland, USA

  Victor R. Basili

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