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Reasoning about Research Quality Alignment in Software Engineering
Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.
Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.ORCID iD: 0000-0003-3818-4442
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering. Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.
Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.
(English)In: Journal of Systems and Software, ISSN 0164-1212, E-ISSN 1873-1228Article in journal (Refereed) Submitted
Abstract [en]

Context: Research quality is intended to assess the design and reporting of studies. It comprises a series of concepts such as methodological rigor, practical relevance, and conformance to ethical standards. Depending on the perspective, different views of importance are given to the conceptual dimensions of research quality.

Objective: We aim to better understand what constitutes research quality from the perspective of the empirical software engineering community. In particular, we intend to assess the level of alignment between researchers with regard to a conceptual model of research quality.

Method: We conducted a mixed methods approach comprising an internal case study and a complementary focus group. We carried out a hierarchical voting prioritization based on the conceptual model to collect relative values for importance. In the focus group, we also moderate discussions with experts to address potential misalignment.

Results: We provide levels of alignment with regard to the importance of quality dimensions in the view of the participants. Moreover, the conceptual model fairly expresses the quality of research but has limitations with regards the structure and description of its components.

Conclusion: Based on the results, we revised the conceptual model and provided an updated version adjusted to the context of empirical software engineering research. We also discussed how to assess quality alignment in research using our approach, and how to use the revised model of quality to characterize an assessment instrument.

Keywords [en]
Research Quality, Alignment, Mixed Method, Case Study, Focus Group
National Category
Software Engineering
Identifiers
URN: urn:nbn:se:bth-17646OAI: oai:DiVA.org:bth-17646DiVA, id: diva2:1292237
Available from: 2019-02-27 Created: 2019-02-27 Last updated: 2019-03-08Bibliographically approved
In thesis
1. Views of Research Quality in Empirical Software Engineering
Open this publication in new window or tab >>Views of Research Quality in Empirical Software Engineering
2019 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Background. Software Engineering (SE) research, like other applied disciplines, intends to provide trustful evidence to practice. To ensure trustful evidence, a rigorous research process based on sound research methodologies is required. Further, to be practically relevant, researchers rely on identifying original research problems that are of interest to industry; and the research must fulfill various quality standards that form the basis for the evaluation of the empirical research in SE. A dialogue and shared view of quality standards for research practice is still to be achieved within the research community.

 Objectives. The main objective of this thesis is to foster dialogue and capture different views of SE researchers on method level (e.g., through the identification and reasoning on the importance of quality characteristics for experiments, surveys and case studies) as well as general quality standards for Empirical Software Engineering (ESE). Given the views of research quality, a second objective is to understand how to operationalize, i.e. build and validate instruments to assess research quality. 

Method. The thesis makes use of a mixed method approach of both qualitative and quantitative nature. The research methods used were case studies, surveys, and focus groups. A range of data collection methods has been employed, such as literature review, questionnaires, and semi-structured workshops. To analyze the data, we utilized content and thematic analysis, descriptive and inferential statistics.

Results. We draw two distinct views of research quality. Through a top-down approach, we assessed and evolved a conceptual model of research quality within the ESE research community. Through a bottom-up approach, we built a checklist instrument for assessing survey-based research grounded on supporting literature and evaluated ours and others’ checklists in research practice and research education contexts.

Conclusion. The quality standards we identified and operationalized support and extend the current understanding of research quality for SE research. This is a preliminary, but still vital, step towards a shared understanding and view of research quality for ESE research. Further steps are needed to gain a shared understanding of research quality within the community. 

Place, publisher, year, edition, pages
Karlskrona: Blekinge Tekniska Högskola, 2019
Series
Blekinge Institute of Technology Doctoral Dissertation Series, ISSN 1653-2090
Keywords
Research Quality, Quality Standards, Empirical Software Engineering, Research Methodology
National Category
Software Engineering
Identifiers
urn:nbn:se:bth-17648 (URN)
Opponent
Supervisors
Available from: 2019-03-05 Created: 2019-02-27 Last updated: 2019-03-05Bibliographically approved

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Molléri, Jefferson SeideFelderer, MichaelMendes, EmiliaPetersen, Kai

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