Dagstuhl Seminar Empirical Software Engineering Issues 2006

Session 1 The Empirical Paradigm

• H. Dieter Rombach:
  The Empirical Paradigm Introduction . 1-3
  

Approaches for Empirical Validation

• Marvin V. Zelkowitz:
  Techniques for Empirical Validation. 4-9
  
• Andreas Höfer, Walter F. Tichy:
  Status of Empirical Research in Software Engineering. 10-19
  

Position Papers

• Marcus Ciolkowski:
  Aggregation of Empirical Evidence. 20
  
• Lionel C. Briand:
  Empirical Evaluation in Software Engineering: Role, Strategy, and Limitations. 21
  
• Markku Oivo:
  New Opportunities for Empirical Research. 22
  
• Carolyn B. Seaman:
  Empirical Paradigm: Position Paper. 23
  
• Austen Rainer:
  The Value of Empirical Evidence for Practitioners and Researchers. 24
  

Exploration Versus Confirmation

• Barbara Kitchenham:
  Empirical Paradigm - The Role of Experiments. 25-32
  
• Victor R. Basili:
  The Role of Controlled Experiments in Software Engineering Research. 33-37
  

Position Papers

• James Miller:
  Creating Real Value in Software Engineering Experiments. 38
  
• Guilherme Horta Travassos:
  From Silver Bullets to Philosophers' Stones: Who Wants to Be Just an Empiricist? 39
  
• Helen Sharp:
  Social and Human Aspects of Software Engineering. 40
  
• Tracy Hall:
  Longitudinal Studies in Evidence-Based Software Engineering. 41
  
• Jeffrey Carver:
  The Use of Grounded Theory in Empirical Software Engineering. 42
  

Historical Review

• Michael S. Mahoney:
  Exploration and Confirmation: An Historical Perspective. 43-49
  

Working Group Results

• Carolyn B. Seaman:
  Combining Study Designs and Techniques Working Group Results. 50-53
  
• Lutz Prechelt:
  Optimizing Return-On-Investment (ROI) for Empirical Software Engineering Studies Working Group Results. 54-57
  
• Andreas Jedlitschka, Lionel C. Briand:
  The Role of Controlled Experiments Working Group Results. 58-62
  

Discussion and Summary

• Marcus Ciolkowski, Barbara Kitchenham, H. Dieter Rombach:
  The Empirical Paradigm Discussion and Summary. 63-67
  

Session 2 Measurement and Model Building

• Victor R. Basili:
  Measurement and Model Building Introduction. 68-69
  

Data Sharing

• Richard W. Selby:
  Data Collection, Analysis, and Sharing Strategies for Enabling Software Measurement and Model Building. 70-76
  
• Dag I. K. Sjøberg:
  Knowledge Acquisition in Software Engineering Requires Sharing of Data and Artifacts. 77-82
  

Effective Data Interpretation

• Jürgen Münch:
  Effective Data Interpretation. 83-90
  
• Audris Mockus:
  Software Support Tools and Experimental Work. 91-99
  

Position Papers

• Hakan Erdogmus:
  Measurement and Interpretation of Productivity and Functional Correctness. 100
  
• Barbara Kitchenham:
  Synthesising Research Results. 101
  
• Thomas J. Ostrand:
  On the Quality of Data. 102
  

Working Group Results

• Nachiappan Nagappan:
  Potential of Open Source Systems as Project Repositories for Empirical Studies Working Group Results. 103-107
  
• Marvin V. Zelkowitz:
  Data Sharing Enabling Technologies Working Group Results. 108-110
  
• Dag I. K. Sjøberg:
  Documenting Theories Working Group Results. 111-114
  

Discussion and Summary

• Sira Vegas, Victor R. Basili:
  Measurement and Model Building Discussion and Summary. 115-120
  

Session 3 Technology Transfer and Education

• Kurt Schneider:
  Technology Transfer and Education Introduction. 121-124
  

Technology Transfer

• Elaine J. Weyuker:
  Empirical Studies as a Basis for Technology Transfer. 125-127
  

Position Papers

• Giovanni Cantone:
  Relationships and Responsibilities of Software Experimentation. 128
  
• Tore Dybå:
  The (Practical) Importance of SE Experiments. 129
  
• Andreas Jedlitschka:
  How to Improve the Use of Controlled Experiments as a Means for Early Technology Transfer. 130
  
• Marek Leszak:
  Extending Empirical Studies to Cover More Realistic Industrial Development and Project Management Issues. 131
  
• Nachiappan Nagappan:
  Empirical Case Studies in Industry: Some Thoughts. 132
  
• Dietmar Pfahl:
  Software Process Simulation Frameworks in Support of Packaging and Transferring Empirical Evidence. 133
  
• Laurie Williams:
  Structuring Families of Industrial Case Studies. 134
  

Education

• Claes Wohlin:
  Empirical Software Engineering: Teaching Methods and Conducting Studies. 135-142
  
• Natalia Juristo Juzgado:
  Educational Objectives for Empirical Methods. 143-150
  

Position Papers

• Frank Houdek:
  On "Landscaping" and Influence of Empirical Studies. 151
  
• Maria Letizia Jaccheri, Sandro Morasca:
  Involving Industry Professionals in Empirical Studies with Students. 152
  

Working Group Results

• Lutz Prechelt, Laurie Williams:
  Industry-Research Collaboration Working Group Results . 153-157
  
• Austen Rainer, Marcus Ciolkowski, Dietmar Pfahl, Barbara Kitchenham, Sandro Morasca, Matthias M. Müller, Guilherme Horta Travassos, Sira Vegas:
  Teaching Empirical Methods to Undergraduate Students Working Group Results. 158-162
  

Discussion and Summary

• Andreas Jedlitschka, Dietmar Pfahl, Kurt Schneider:
  Technology Transfer and Education Discussion and Summary. 163-167
  

Roadmapping

• Richard W. Selby:
  Empirical Software Engineering Research Roadmap Introduction. 168-171
  

Working Group Results

• D. Ross Jeffery:
  Roadmapping Working Group 1 Results. 172-174
  
• Marcus Ciolkowski, Lionel C. Briand:
  Roadmapping Working Group 2 Results. 175-177
  
• Frank Houdek:
  Roadmapping Working Group 3 Results. 178-180
  
• Laurie Williams, Hakan Erdogmus, Richard W. Selby:
  Roadmapping Working Group 4 Results. 181-183
  

Discussion and Summary

• Richard W. Selby:
  Empirical Software Engineering Research Roadmap Discussion and Summary. 184-187
  

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