Experimentation in Software Engineering

By Claes Wohlin, Per Runeson, Martin Höst, Magnus C. Ohlsson, Björn Regnell, Anders Wesslén. Springer Berlin Heidelberg, 2012

5,000 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Information Systems

View Paper: https://www.semanticscholar.org/paper/b7618a812e21f965edd784e6fea98f02ebe54f0a

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In Computer Networks and Communications

In Information Systems

Citations in the corpus

GitHub Copilot AI pair programmer: Asset or Liability? (2022, methodology): “We now discuss the threats to the validity of our study following the guidelines provided by Wohlin [54] for experimentation in software engineering.”
A practical guide to controlled experiments of software engineering tools with human participants (2013, methodology): “Methodological literature instead focuses on other important but more general issues, providing conceptual background on experiments, measurement, and research design (e.g., Wohlin et al. 2000; Easterbrook et al. 2008; Shull et al. 2006; Juristo and Moreno 2001; Kitchenham et al. 2002).”
In-IDE Code Generation from Natural Language: Promise and Challenges (2021, methodology): “Following best practices for empirical software engineering research [104, 114], we make our study fully replicable, publishing our plugin prototype, instrumented virtual environment, the different scripts for data extraction and analysis, and the obtained anonymized raw data; see the online appendi”
Sampling in software engineering research: a critical review and guidelines (2020, methodology): “Most general methods textbooks, such a Trochim’s excellent Research Methods Knowledge Base (Trochim and Donnelly 2001) and SE-specific methods texts (e.g. Wohlin et al. 2012; Foster 2014; Easterbrook et al. 2008) discuss the logic of sampling, and many of the strategies described in Section 2.”
Recommendation Systems in Software Engineering (2014, background): “In software engineering scenarios, typical questions that can be answered with the support of recommendation systems are, for example, which software changes probably introduce a bug? [3], which requirements to implement in the next software release? [25], which stakeholders should participate in th”
Guidelines for conducting systematic mapping studies in software engineering: An update (2015, methodology): “[67] describe the following set of research methodologies that are frequently applied in software engineering: Survey, case study, controlled experiment, action research, ethnography, simulation, prototyping, and mathematical analysis.”
Guidelines for including the grey literature and conducting multivocal literature reviews in software engineering (2017, background): “As SE is an application-oriented research field [51], where a large number of software practitioners constantly produces a huge wealth of valuable GL knowledge, utilizing that knowledge in research activities is important.”
A Hitchhiker's guide to statistical tests for assessing randomized algorithms in software engineering (2014, background): “There are also guidelines for running an experiment with human subjects in software engineering [25].”
How-to conduct a systematic literature review: A quick guide for computer science research (2022, background): “Obtaining opinions from peers while developing the protocol, is encouraged to ensure the review’s consistency and validity, and helps identify when modiﬁcations are necessary [20] .”
Tailored gamification in education: A literature review and future agenda (2022, methodology): “We classified the threats to validity using the Internal, External, Construct, and Conclusion categories of Wohlin et al. (2012).”