Reporting guidelines for controlled experiments in software engineering
By Andreas Jedlitschka, Dietmar Pfahl. International Symposium on Empirical Software Engineering, 2005
296 citations recorded by the source corpus.
Subfields: Information Systems, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/7d543cf8af92580e398f60f5d1a924962ea68baa
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Information Systems
- Per Runeson
- Martin Höst
- Emelie Engström
- Mats Skoglund
- Emilia Mendes
- Claes Wohlin
- Wannisa Matcha
- Nora'ayu Ahmad Uzir
In Statistics and Probability
- Per Runeson
- Emelie Engström
- Mats Skoglund
- Martin Höst
- Wannisa Matcha
- Emilia Mendes
- Nora'ayu Ahmad Uzir
- Dietmar Pfahl
Citations in the corpus
- A Systematic Review of Empirical Studies on Learning Analytics Dashboards: A Self-Regulated Learning Perspective (2020, background): “We particularly refer to some technology-related fields such as empirical software engineering from which empirical research on user-centered learning analytics systems can learn and which have guidelines how results should be reported and threats to validity discussed [99], [100].”
- Empirical Studies of Pair Programming for CS/SE Teaching in Higher Education: A Systematic Literature Review (2011, background): “In order to improve the quality of empirical research, researchers can refer to available guidelines for conducting empirical research in SE [37] and for reporting controlled experiments in SE [30].”
- A systematic review on regression test selection techniques (2010, methodology): “Jedlitschka and Pfahl [24]for experiments and Runeson and Höst [52] for case studies.”
- Experimentation in Software Engineering (2012, methodology): “Jedlitschka and Pfahl propose a scheme for the academic reporting of experiments [86] which was later evaluated by Kitchenham et al.”
- Guidelines for conducting and reporting case study research in software engineering (2009, background): “…2) its conclusions are based on a clear chain of evidence, whether qualitative or quantitative, collected from multiple sources in a planned and consistent manner, and 3) it adds to existing knowledge by being based on previously established theory, if such exist, or by building theory.”
- Reporting Experiments in Software Engineering (2008, background): “Conclusion: The resulting checklist provides detailed guidance on the expected content of the sections and subsections for reporting a specific type of empirical studies, i.e., experiments (controlled experiments and quasi-experiments).”