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Views of Research Quality in Empirical Software Engineering
Blekinge Institute of Technology, Faculty of Computing, Department of 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 ; 7
Keywords [en]
Research Quality, Quality Standards, Empirical Software Engineering, Research Methodology
National Category
Software Engineering
Identifiers
URN: urn:nbn:se:bth-17648ISBN: 978-91-7295-372-7 (print)OAI: oai:DiVA.org:bth-17648DiVA, id: diva2:1292254
Public defence
2019-06-14, J1650, Campus Gräsvik, Karlskrona, 13:00 (English)
Opponent
Supervisors
Available from: 2019-03-05 Created: 2019-02-27 Last updated: 2019-05-09Bibliographically approved
List of papers
1. Towards understanding the relation between citations and research quality in software engineering studies
Open this publication in new window or tab >>Towards understanding the relation between citations and research quality in software engineering studies
2018 (English)In: Scientometrics, ISSN 0138-9130, E-ISSN 1588-2861Article in journal (Refereed) Epub ahead of print
Abstract [en]

The importance of achieving high quality in research practice has been highlighted in different disciplines. At the same time, citations are utilized to measure the impact of academic researchers and institutions. One open question is whether the quality in the reporting of research is related to scientific impact, which would be desired. In this exploratory study we aim to: (1) Investigate how consistently a scoring rubric for rigor and relevance has been used to assess research quality of software engineering studies; (2) Explore the relationship between rigor, relevance and citation count. Through backward snowball sampling we identified 718 primary studies assessed through the scoring rubric. We utilized cluster analysis and conditional inference tree to explore the relationship between quality in the reporting of research (represented by rigor and relevance) and scientiometrics (represented by normalized citations). The results show that only rigor is related to studies’ normalized citations. Besides that, confounding factors are likely to influence the number of citations. The results also suggest that the scoring rubric is not applied the same way by all studies, and one of the likely reasons is because it was found to be too abstract and in need to be further refined. Our findings could be used as a basis to further understand the relation between the quality in the reporting of research and scientific impact, and foster new discussions on how to fairly acknowledge studies for performing well with respect to the emphasized research quality. Furthermore, we highlighted the need to further improve the scoring rubric. © 2018, The Author(s).

Place, publisher, year, edition, pages
Springer Netherlands, 2018
Keywords
Conditional inference tree, Empirical software engineering, Exploratory study, Reporting of research, Research practice, Scientific impact
National Category
Software Engineering
Identifiers
urn:nbn:se:bth-17086 (URN)10.1007/s11192-018-2907-3 (DOI)2-s2.0-85053837175 (Scopus ID)
Available from: 2018-10-05 Created: 2018-10-05 Last updated: 2019-04-24Bibliographically approved
2. CERSE - Catalog for empirical research in software engineering: A Systematic mapping study
Open this publication in new window or tab >>CERSE - Catalog for empirical research in software engineering: A Systematic mapping study
2019 (English)In: Information and Software Technology, ISSN 0950-5849, E-ISSN 1873-6025, Vol. 105, p. 117-149Article in journal (Refereed) Published
Abstract [en]

Context Empirical research in software engineering contributes towards developing scientific knowledge in this field, which in turn is relevant to inform decision-making in industry. A number of empirical studies have been carried out to date in software engineering, and the need for guidelines for conducting and evaluating such research has been stressed. Objective: The main goal of this mapping study is to identify and summarize the body of knowledge on research guidelines, assessment instruments and knowledge organization systems on how to conduct and evaluate empirical research in software engineering. Method: A systematic mapping study employing manual search and snowballing techniques was carried out to identify the suitable papers. To build up the catalog, we extracted and categorized information provided by the identified papers. Results: The mapping study comprises a list of 341 methodological papers, classified according to research methods, research phases covered, and type of instrument provided. Later, we derived a brief explanatory review of the instruments provided for each of the research methods. Conclusion: We provide: an aggregated body of knowledge on the state of the art relating to guidelines, assessment instruments and knowledge organization systems for carrying out empirical software engineering research; an exemplary usage scenario that can be used to guide those carrying out such studies is also provided. Finally, we discuss the catalog's implications for research practice and the needs for further research. © 2018 Elsevier B.V.

Place, publisher, year, edition, pages
Elsevier B.V., 2019
Keywords
Empirical methods, Empirical research, Mapping study, Decision making, Mapping, Software engineering, Assessment instruments, Empirical method, Empirical research in software engineering, Empirical Software Engineering, Knowledge organization systems, Mapping studies, Systematic mapping studies, Knowledge management
National Category
Software Engineering
Identifiers
urn:nbn:se:bth-17108 (URN)10.1016/j.infsof.2018.08.008 (DOI)000452586900008 ()2-s2.0-85054061108 (Scopus ID)
Available from: 2018-10-11 Created: 2018-10-11 Last updated: 2019-04-24Bibliographically approved
3. Reasoning about Research Quality Alignment in Software Engineering
Open this publication in new window or tab >>Reasoning about Research Quality Alignment in 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
Research Quality, Alignment, Mixed Method, Case Study, Focus Group
National Category
Software Engineering
Identifiers
urn:nbn:se:bth-17646 (URN)
Available from: 2019-02-27 Created: 2019-02-27 Last updated: 2019-03-08Bibliographically approved
4. An Empirically Evaluated Checklist for Surveys in Software Engineering
Open this publication in new window or tab >>An Empirically Evaluated Checklist for Surveys in Software Engineering
(English)In: Information and Software Technology, ISSN 0950-5849, E-ISSN 1873-6025Article in journal (Refereed) Submitted
Abstract [en]

Context: Over the past decade Software Engineering research has seen a steady increase in survey-based studies, and there are several guidelines providing support for those willing to carry out surveys. The need for auditing survey research has been raised in the literature. Checklists have been used to assess different types of empirical studies, such as experiments and case studies.

Objective: This paper proposes a checklist to support the design and assessment of survey-based research in software engineering grounded in existing guidelines for survey research. We further evaluated the checklist in the research practice context.

Method: To construct the checklist, we systematically aggregated knowledge from 12 methodological studies supporting survey-based research in software engineering. We identified the key stages of the survey process and its recommended practices through thematic analysis and vote counting. To improve our initially designed checklist we evaluated it using a mixed evaluation approach involving experienced researchers.

Results: The evaluation provided insights regarding the limitations of the checklist in relation to its understanding and objectivity. In particular, 19 of the 38 checklist items were improved according to the feedback received from its evaluation. Finally, a discussion on how to use the checklist and what its implications are for research practice is also provided.

Conclusion: The proposed checklist is an instrument suitable for auditing survey reports as well as a support tool to guide ongoing research with regard to the survey design process.

Keywords
Checklist, Assessment, Survey, Methodology
National Category
Software Engineering
Identifiers
urn:nbn:se:bth-17645 (URN)
Available from: 2019-02-27 Created: 2019-02-27 Last updated: 2019-04-24Bibliographically approved
5. Teaching students critical appraisal of scientific literature using checklists
Open this publication in new window or tab >>Teaching students critical appraisal of scientific literature using checklists
Show others...
2018 (English)In: PROCEEDINGS OF THE 3RD EUROPEAN CONFERENCE OF SOFTWARE ENGINEERING EDUCATION (ECSEE), Association for Computing Machinery , 2018, p. 8-17Conference paper, Published paper (Refereed)
Abstract [en]

Background: Teaching students to critically appraise scientific literature is an important goal for a postgraduate research methods course. Objective: To investigate the application of checklists for assessing the scientific rigor of empirical studies support students in reviewing case study research and experiments. Methods:We employed an experimental design where 76 students (in pairs) used two checklists to evaluate two papers (reporting a case study and an experiment) each. We compared the students' assessments against ratings from more senior researchers. We also collected data on students' perception of using the checklists. Results: The consistency of students' ratings and the accuracy when compared to ratings from seniors varied. A factor seemed to be that the clearer the reporting, the easier it is for students to judge the quality of studies. Students perceived checklist items related to data analysis as difficult to assess. Conclusion: As expected, this study reinforces the needs for clear reporting, as it is important that authors write to enable synthesis and quality assessment. With clearer reporting, the novices performed well in assessing the quality of the empirical work, which supports its continued use in the course as means for introducing scientific reviews. © 2018 Association for Computing Machinery.

Place, publisher, year, edition, pages
Association for Computing Machinery, 2018
Keywords
Case study, Checklist, Critical appraisal, Experiment, Student, Design of experiments, Engineering education, Experiments, Software engineering, Teaching, Case study research, Continued use, Empirical studies, Post-graduate research, Quality assessment, Scientific literature, Students
National Category
Software Engineering
Identifiers
urn:nbn:se:bth-16892 (URN)10.1145/3209087.3209099 (DOI)000478670000002 ()2-s2.0-85049867400 (Scopus ID)9781450363839 (ISBN)
Conference
3rd European Conference of Software Engineering Education, ECSEE, Seeon Monastery, Germany
Available from: 2018-08-20 Created: 2018-08-20 Last updated: 2019-09-10Bibliographically approved

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Molléri, Jefferson Seide

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