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Börstler, Jürgen, ProfessorORCID iD iconorcid.org/0000-0003-0639-4234
Publications (10 of 115) Show all publications
Tran, H. K., Ali, N. b., Unterkalmsteiner, M., Börstler, J. & Chatzipetrou, P. (2025). Quality attributes of test cases and test suites - importance & challenges from practitioners' perspectives. Software quality journal, 33(1), Article ID 9.
Open this publication in new window or tab >>Quality attributes of test cases and test suites - importance & challenges from practitioners' perspectives
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2025 (English)In: Software quality journal, ISSN 0963-9314, E-ISSN 1573-1367, Vol. 33, no 1, article id 9Article in journal (Refereed) Published
Abstract [en]

The quality of the test suites and the constituent test cases significantly impacts confidence in software testing. While research has identified several quality attributes of test cases and test suites, there is a need for a better understanding of their relative importance in practice. We investigate practitioners' perceptions regarding the relative importance of quality attributes of test cases and test suites and the challenges that they face in ensuring the perceived important quality attributes. To capture the practitioners' perceptions, we conducted an industrial survey using a questionnaire based on the quality attributes identified in an extensive literature review. We used a sampling strategy that leverages LinkedIn to draw a large and heterogeneous sample of professionals with experience in software testing. We collected 354 responses from practitioners with a wide range of experience (from less than one year to 42 years of experience). We found that the majority of practitioners rated Fault Detection, Usability, Maintainability, Reliability, and Coverage to be the most important quality attributes. Resource Efficiency, Reusability, and Simplicity received the most divergent opinions, which, according to our analysis, depend on the software-testing contexts. Also, we identified common challenges that apply to the important attributes, namely inadequate definition, lack of useful metrics, lack of an established review process, and lack of external support. The findings point out where practitioners actually need further support with respect to achieving high-quality test cases and test suites under different software testing contexts. Hence, the findings can serve as a guideline for academic researchers when looking for research directions on the topic. Furthermore, the findings can be used to encourage companies to provide more support to practitioners to achieve high-quality test cases and test suites.

Place, publisher, year, edition, pages
Springer, 2025
Keywords
Software testing, Test case quality, Test suite quality, Quality assurance
National Category
Software Engineering
Identifiers
urn:nbn:se:bth-27395 (URN)10.1007/s11219-024-09698-w (DOI)001396622900001 ()
Funder
ELLIIT - The Linköping‐Lund Initiative on IT and Mobile CommunicationsKnowledge Foundation, 20220235Knowledge Foundation, 20180010
Available from: 2025-01-24 Created: 2025-01-24 Last updated: 2025-01-24Bibliographically approved
Iftikhar, U., Ali, N. b., Börstler, J. & Usman, M. (2024). A tertiary study on links between source code metrics and external quality attributes. Information and Software Technology, 165, Article ID 107348.
Open this publication in new window or tab >>A tertiary study on links between source code metrics and external quality attributes
2024 (English)In: Information and Software Technology, ISSN 0950-5849, E-ISSN 1873-6025, Vol. 165, article id 107348Article, review/survey (Refereed) Published
Abstract [en]

Context: Several secondary studies have investigated the relationship between internal quality attributes, source code metrics and external quality attributes. Sometimes they have contradictory results. Objective: We synthesize evidence of the link between internal quality attributes, source code metrics and external quality attributes along with the efficacy of the prediction models used. Method: We conducted a tertiary review to identify, evaluate and synthesize secondary studies. We used several characteristics of secondary studies as indicators for the strength of evidence and considered them when synthesizing the results. Results: From 711 secondary studies, we identified 15 secondary studies that have investigated the link between source code and external quality. Our results show : (1) primarily, the focus has been on object-oriented systems, (2) maintainability and reliability are most often linked to internal quality attributes and source code metrics, with only one secondary study reporting evidence for security, (3) only a small set of complexity, coupling, and size-related source code metrics report a consistent positive link with maintainability and reliability, and (4) group method of data handling (GMDH) based prediction models have performed better than other prediction models for maintainability prediction. Conclusions: Based on our results, lines of code, coupling, complexity and the cohesion metrics from Chidamber & Kemerer (CK) metrics are good indicators of maintainability with consistent evidence from high and moderate-quality secondary studies. Similarly, four CK metrics related to coupling, complexity and cohesion are good indicators of reliability, while inheritance and certain cohesion metrics show no consistent evidence of links to maintainability and reliability. Further empirical studies are needed to explore the link between internal quality attributes, source code metrics and other external quality attributes, including functionality, portability, and usability. The results will help researchers and practitioners understand the body of knowledge on the subject and identify future research directions. © 2023 The Author(s)

Place, publisher, year, edition, pages
Elsevier, 2024
Keywords
Code quality, Evidence, Product quality, Quality models, Tertiary review, Tertiary study, Codes (symbols), Computer programming languages, Data handling, Forecasting, Object oriented programming, Reliability, External quality, Internal quality, Products quality, Quality attributes, Quality modeling, Source code metrics, Maintainability
National Category
Software Engineering
Identifiers
urn:nbn:se:bth-25555 (URN)10.1016/j.infsof.2023.107348 (DOI)001102357100001 ()2-s2.0-85174715019 (Scopus ID)
Funder
ELLIIT - The Linköping‐Lund Initiative on IT and Mobile CommunicationsKnowledge Foundation, 20190081
Available from: 2023-11-06 Created: 2023-11-06 Last updated: 2024-03-13Bibliographically approved
Börstler, J., Ali, N. b., Petersen, K. & Engström, E. (2024). Acceptance behavior theories and models in software engineering — A mapping study. Information and Software Technology, 172, Article ID 107469.
Open this publication in new window or tab >>Acceptance behavior theories and models in software engineering — A mapping study
2024 (English)In: Information and Software Technology, ISSN 0950-5849, E-ISSN 1873-6025, Vol. 172, article id 107469Article in journal (Refereed) Published
Abstract [en]

Context: The adoption or acceptance of new technologies or ways of working in software development activities is a recurrent topic in the software engineering literature. The topic has, therefore, been empirically investigated extensively. It is, however, unclear which theoretical frames of reference are used in this research to explain acceptance behaviors. Objective: In this study, we explore how major theories and models of acceptance behavior have been used in the software engineering literature to empirically investigate acceptance behavior.Method: We conduct a systematic mapping study of empirical studies using acceptance behavior theories in software engineering.Results: We identified 47 primary studies covering 56 theory uses. The theories were categorized into six groups. Technology acceptance models (TAM and its extensions) were used in 29 of the 47 primary studies, innovation theories in 10, and the theories of planned behavior/ reasoned action (TPB/TRA) in six. All other theories were used in at most two of the primary studies. The usage and operationalization of the theories were, in many cases, inconsistent with the underlying theories. Furthermore, we identified 77 constructs used by these studies of which many lack clear definitions. Conclusions: Our results show that software engineering researchers are aware of some of the leading theories and models of acceptance behavior, which indicates an attempt to have more theoretical foundations. However, we identified issues related to theory usage that make it difficult to aggregate and synthesize results across studies. We propose mitigation actions that encourage the consistent use of theories and emphasize the measurement of key constructs.

Place, publisher, year, edition, pages
Elsevier, 2024
Keywords
Acceptance behavior, Technology adoption, Theory use in software engineering, TAM, TPB, TRA, Fitness, Innovation diffusion
National Category
Software Engineering
Research subject
Software Engineering
Identifiers
urn:nbn:se:bth-26143 (URN)10.1016/j.infsof.2024.107469 (DOI)001233663200001 ()2-s2.0-85190986067 (Scopus ID)
Projects
ELLIIT
Funder
ELLIIT - The Linköping‐Lund Initiative on IT and Mobile CommunicationsKnowledge Foundation, 20220235
Available from: 2024-04-24 Created: 2024-04-24 Last updated: 2024-06-18Bibliographically approved
Iftikhar, U., Börstler, J., Ali, N. b. & Kopp, O. (2024). Identifying prevalent quality issues in code changes by analyzing reviewers' feedback.
Open this publication in new window or tab >>Identifying prevalent quality issues in code changes by analyzing reviewers' feedback
2024 (English)Manuscript (preprint) (Other academic)
Abstract [en]

Context: Code reviewers provide valuable feedback during the code review. Identifying common issues described in the reviewers' feedback can provide input for context-specific software improvement opportunities. However, the use of reviewer feedback for this purpose is currently less explored.

Objective: Assessing if and how automation can derive themes in reviewers' feedback and whether these themes help to identify recurring quality-related issues in code changes.

Method: We conducted a case study using the JabRef system to distinguish reviewers' feedback on merged and abandoned code changes for the analysis. We used topic modeling to identify themes in 5,560 code review comments. The resulting themes were analyzed and named by a domain expert from JabRef.

Results: The domain expert considered the identified themes from the proposed automation approach to represent quality-related issues. We found that different quality issues are pointed out in code reviews for merged and abandoned code changes. 

Conclusions: The results indicate the usefulness of our proposed automation approach in utilizing code review comments for understanding the prevalent code quality issues that can help derive targeted and context-bound improvement actions.

National Category
Computer Systems
Research subject
Software Engineering
Identifiers
urn:nbn:se:bth-25611 (URN)
Funder
ELLIIT - The Linköping‐Lund Initiative on IT and Mobile Communications
Available from: 2024-01-23 Created: 2024-01-23 Last updated: 2024-03-13Bibliographically approved
Laiq, M., Ali, N. b., Börstler, J. & Engström, E. (2024). Industrial adoption of machine learning techniques for early identification of invalid bug reports. Empirical Software Engineering, 29(5), Article ID 130.
Open this publication in new window or tab >>Industrial adoption of machine learning techniques for early identification of invalid bug reports
2024 (English)In: Empirical Software Engineering, ISSN 1382-3256, E-ISSN 1573-7616, Vol. 29, no 5, article id 130Article in journal (Refereed) Published
Abstract [en]

Despite the accuracy of machine learning (ML) techniques in predicting invalid bug reports, as shown in earlier research, and the importance of early identification of invalid bug reports in software maintenance, the adoption of ML techniques for this task in industrial practice is yet to be investigated. In this study, we used a technology transfer model to guide the adoption of an ML technique at a company for the early identification of invalid bug reports. In the process, we also identify necessary conditions for adopting such techniques in practice. We followed a case study research approach with various design and analysis iterations for technology transfer activities. We collected data from bug repositories, through focus groups, a questionnaire, and a presentation and feedback session with an expert. As expected, we found that an ML technique can identify invalid bug reports with acceptable accuracy at an early stage. However, the technique’s accuracy drops over time in its operational use due to changes in the product, the used technologies, or the development organization. Such changes may require retraining the ML model. During validation, practitioners highlighted the need to understand the ML technique’s predictions to trust the predictions. We found that a visual (using a state-of-the-art ML interpretation framework) and descriptive explanation of the prediction increases the trustability of the technique compared to just presenting the results of the validity predictions. We conclude that trustability, integration with the existing toolchain, and maintaining the techniques’ accuracy over time are critical for increasing the likelihood of adoption. © The Author(s) 2024.

Place, publisher, year, edition, pages
Springer, 2024
Keywords
Concept drift, Defect classification, Invalid bug reports, Machine learning, Software maintenance, Software quality, Computer software maintenance, Computer software selection and evaluation, Industrial research, Technology transfer, Bug reports, Concept drifts, Industrial adoption, Industrial practices, Invalid bug report, Machine learning techniques, Machine-learning, Transfer models, Forecasting
National Category
Software Engineering
Identifiers
urn:nbn:se:bth-26802 (URN)10.1007/s10664-024-10502-3 (DOI)001283245300001 ()2-s2.0-85200034314 (Scopus ID)
Funder
ELLIIT - The Linköping‐Lund Initiative on IT and Mobile CommunicationsKnowledge Foundation, 20220235
Available from: 2024-08-14 Created: 2024-08-14 Last updated: 2024-12-03Bibliographically approved
Izu, C., Mirolo, C., Börstler, J., Connamacher, H., Crosby, R., Glassey, R., . . . Shah, A. (2024). Introducing Code Quality at CS1 Level: Examples and Activities. In: Proceedings of the 29th Annual Conference on Innovation and Technology in Computer Science Education: Working Group Reports. Paper presented at Annual Conference on Innovation and Technology in Computer Science Education (ITiCSE), Milan, July 8-10, 2024 (pp. 339-377). Association for Computing Machinery (ACM)
Open this publication in new window or tab >>Introducing Code Quality at CS1 Level: Examples and Activities
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2024 (English)In: Proceedings of the 29th Annual Conference on Innovation and Technology in Computer Science Education: Working Group Reports, Association for Computing Machinery (ACM), 2024, p. 339-377Conference paper, Published paper (Refereed)
Abstract [en]

Characterising code quality is a challenge that was addressed by a previous ITiCSE Working Group (Börstler et al., 2017). As emerged from that study, educators, developers, and students have different perceptions of the aspects involved. The perception of code quality by CS1 students develops from the feedback they receive when submitting practical work. As a consequence of increasingly large classes and the widespread use of autograders, student code is predominantly assessed based on functional correctness, emphasising a machine-oriented perspective with scarce or no feedback given about human-oriented aspects of code quality. Such limited perception of code quality may negatively impact how students understand, create, and interact with code artefacts. Although Börstler et al. concluded that "code quality should be discussed more thoroughly in educational programs", the lack of materials and time constraints have slowed down progress in that regard. The goal of this Working Group is to support CS1 instructors who want to introduce a broader perspective on code quality in their classroom by providing a curated list of examples and activities suitable for novices. In order to achieve this goal, we have extracted from the CS education literature a range of examples and activities, which have then been analyzed and organized in terms of code quality dimensions. We have also mapped the topics covered in those materials to existing taxonomies relevant to code quality in CS1. Based on this work, we provide (1) a catalog of examples that illustrates the range of quality defects that could be addressed at the CS1 level and (2) a sample set of activities devised to introduce code quality to CS1 students. These materials have the potential to help educators address the subject in more depth.

Place, publisher, year, edition, pages
Association for Computing Machinery (ACM), 2024
National Category
Didactics Computer Sciences Software Engineering
Research subject
Software Engineering
Identifiers
urn:nbn:se:bth-27456 (URN)10.1145/3689187.3709615 (DOI)
Conference
Annual Conference on Innovation and Technology in Computer Science Education (ITiCSE), Milan, July 8-10, 2024
Available from: 2025-02-14 Created: 2025-02-14 Last updated: 2025-02-18Bibliographically approved
Izu, C., Mirolo, C., Börstler, J., Connamacher, H., Crosby, R., Glassey, R., . . . Shah, A. (2024). Introducing Code Quality in the CS1 Classroom. In: Proceedings of the 2024 Conference on Innovation and Technology in Computer Science Education, vol 2,  ITiCSE 2024: . Paper presented at 29th Annual Conference on Innovation and Technology in Computer Science Education, ITiCSE 2024, Milan, July 8-10 2024 (pp. 773-774). Association for Computing Machinery (ACM), 2
Open this publication in new window or tab >>Introducing Code Quality in the CS1 Classroom
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2024 (English)In: Proceedings of the 2024 Conference on Innovation and Technology in Computer Science Education, vol 2,  ITiCSE 2024, Association for Computing Machinery (ACM), 2024, Vol. 2, p. 773-774Conference paper, Published paper (Refereed)
Abstract [en]

Characterising code quality is a challenge that was addressed by Börstler et al.’s working group in 2017. As emerged from their study, educators, developers and students have different perceptions of the manifold aspects involved, and a major conclusion of that WG was that “code quality should be discussed more thoroughly in educational programs” [2, p. 70]. However, the lack of materials and the time constraints have slowed down progress in that regard. The goal of this working group is to propose manageable ways to address code quality in the CS1 classroom, with a particular focus on activities that help students become aware of and improve the quality of their code. To achieve this goal, we will (a) extract from the literature a comprehensive set of quality issues which will then be classified according to the appropriate strategies to fix them; and (b) circulate a survey to explore the instructors’ views on code quality issues and the way they deal with (or ignore) them. Based on this work we aim to produce: (1) a taxonomy of code quality issues with associated examples, as well as (2) a sample set of teaching materials to introduce those issues to CS1 students. © 2024 Copyright held by the owner/author(s)

Place, publisher, year, edition, pages
Association for Computing Machinery (ACM), 2024
Series
Annual Conference on Innovation and Technology in Computer Science Education, ITiCSE, ISSN 1942647X
Keywords
code quality, CS1, readability, refactoring, style, Address code, Classifieds, Educational program, Quality issues, Refactorings, Time constraints, Working groups, Students
National Category
Educational Sciences Software Engineering
Identifiers
urn:nbn:se:bth-26773 (URN)10.1145/3649405.3659535 (DOI)001265872800010 ()2-s2.0-85198638608 (Scopus ID)9798400706035 (ISBN)
Conference
29th Annual Conference on Innovation and Technology in Computer Science Education, ITiCSE 2024, Milan, July 8-10 2024
Available from: 2024-08-09 Created: 2024-08-09 Last updated: 2025-02-18Bibliographically approved
Petersen, K., Börstler, J., Ali, N. b. & Engström, E. (2024). Revisiting the construct and assessment of industrial relevance in software engineering research. In: Proceedings - 2024 IEEE/ACM International Workshop on Methodological Issues with Empirical Studies in Software Engineering, WSESE 2024: . Paper presented at 1st International Workshop on Methodological Issues with Empirical Studies in Software Engineering, WSESE 2024, Lisbon, April 16, 2024 (pp. 17-20). Association for Computing Machinery (ACM)
Open this publication in new window or tab >>Revisiting the construct and assessment of industrial relevance in software engineering research
2024 (English)In: Proceedings - 2024 IEEE/ACM International Workshop on Methodological Issues with Empirical Studies in Software Engineering, WSESE 2024, Association for Computing Machinery (ACM), 2024, p. 17-20Conference paper, Published paper (Refereed)
Abstract [en]

Industrial relevance is essential for an applied research area like software engineering. However, it is unclear how to achieve industrial relevance and how we communicate and assess it. We propose a reasoning framework to support the design, reporting, and assessment of research for industrial relevance. © 2024 Copyright is held by the owner/author(s). Publication rights licensed to ACM.

Place, publisher, year, edition, pages
Association for Computing Machinery (ACM), 2024
Keywords
Engineering research, Applied research, Reasoning framework, Research areas, Software engineering research, Industrial research
National Category
Software Engineering
Identifiers
urn:nbn:se:bth-26912 (URN)10.1145/3643664.3648205 (DOI)001293147200004 ()2-s2.0-85203105590 (Scopus ID)9798400705670 (ISBN)
Conference
1st International Workshop on Methodological Issues with Empirical Studies in Software Engineering, WSESE 2024, Lisbon, April 16, 2024
Funder
ELLIIT - The Linköping‐Lund Initiative on IT and Mobile CommunicationsKnowledge Foundation, 20220235
Available from: 2024-09-16 Created: 2024-09-16 Last updated: 2024-10-03Bibliographically approved
Laiq, M., Ali, N. b., Börstler, J. & Engström, E. (2024). Software analytics for software engineering: A tertiary review.
Open this publication in new window or tab >>Software analytics for software engineering: A tertiary review
2024 (English)Report (Other academic)
Abstract [en]

Software analytics (SA) is frequently proposed as a tool to support practitioners in software engineering (SE) tasks. We have observed that several secondary studies on SA have been published. Some of these studies have overlapping aims and some have even been published in the same calendar year. This presents an opportunity to analyze the congruence or divergence of the conclusions in these studies. Such an analysis can help identify broader generalizations beyond any of the individual secondary studies. We identified five secondary studies on the use of SA for SE. These secondary studies cover primary research from 2000 to 2021. Despite the overlapping objectives and search time frames of these secondary studies, there is negligible overlap of primary studies between these secondary studies. Thus, each of them provides an isolated view, and together, they provide a fragmented view, i.e., there is no “common picture” of the area. Thus, we conclude that an overview of the literature identified by these secondary studies would be useful in providing a more comprehensive overview of the topic.

Publisher
p. 14
Keywords
Software engineering, Software analytics, Tertiary review, Machine learning, Data analytics, Visual analytics
National Category
Software Engineering
Research subject
Software Engineering; Software Engineering
Identifiers
urn:nbn:se:bth-27192 (URN)
Funder
ELLIIT - The Linköping‐Lund Initiative on IT and Mobile Communications
Available from: 2024-12-03 Created: 2024-12-03 Last updated: 2025-01-15Bibliographically approved
Iftikhar, U., Ali, N. b., Börstler, J. & Usman, M. (2023). A catalog of source code metrics – a tertiary study. In: Daniel Mendez, Dietmar Winkler, Johannes Kross, Stefan Biffl, Johannes Bergsmann (Ed.), Software Quality: Higher Software Quality through Zero Waste Development. Paper presented at 15th International Conference on Software Quality, SWQD 2023, Munich, Germany, May 23-25, 2023 (pp. 87-106). Springer, 472
Open this publication in new window or tab >>A catalog of source code metrics – a tertiary study
2023 (English)In: Software Quality: Higher Software Quality through Zero Waste Development / [ed] Daniel Mendez, Dietmar Winkler, Johannes Kross, Stefan Biffl, Johannes Bergsmann, Springer, 2023, Vol. 472, p. 87-106Conference paper, Published paper (Refereed)
Abstract [en]

Context: A large number of source code metrics are reported in the literature. It is necessary to systematically collect, describe and classify source code metrics to support research and practice.Objective: We aim to utilize existing secondary studies to develop a cat- alog of source code metrics together with their descriptions. The catalog will also provide information about which units of code (e.g., operators, operands, lines of code, variables, parameters, code blocks, or functions) are used to measure the internal quality attributes and the scope on which they are collected. 

Method: We conducted a tertiary study to identify secondary studies re- porting source code metrics. We have classified the source code metrics according to the measured internal quality attributes, the units of code used in the measures, and the scope at which the source code metrics are collected. 

Results: From 711 secondary studies, we identified 52 relevant secondary studies. We reported 423 source code metrics together with their de- scriptions and the internal quality attributes they measure. Source code metrics predominantly incorporate function as a unit of code to measure internal quality attributes. In contrast, several source code metrics use more than one unit of code when measuring internal quality attributes. Nearly 51% of the source code metrics are collected at the class scope, while almost 12% and 15% of source code metrics are collected at module and application levels, respectively. 

Conclusions: Researchers and practitioners can use the extensive catalog to assess which source code metrics meet their individual needs based on the description and classification scheme presented. 

Place, publisher, year, edition, pages
Springer, 2023
Series
Lecture Notes in Business Information Processing, ISSN 1865-1348, E-ISSN 1865-1356 ; 472
Keywords
Internal quality attributes, Code measurement, Code quality, Ter- tiary study, Source code metrics
National Category
Software Engineering
Research subject
Software Engineering
Identifiers
urn:nbn:se:bth-24650 (URN)10.1007/978-3-031-31488-9_5 (DOI)001269092500005 ()2-s2.0-85161231906 (Scopus ID)978-3-031-31487-2 (ISBN)978-3-031-31488-9 (ISBN)
Conference
15th International Conference on Software Quality, SWQD 2023, Munich, Germany, May 23-25, 2023
Funder
ELLIIT - The Linköping‐Lund Initiative on IT and Mobile Communications, B07Knowledge Foundation, 20190081
Available from: 2023-05-30 Created: 2023-05-30 Last updated: 2024-09-11Bibliographically approved
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ORCID iD: ORCID iD iconorcid.org/0000-0003-0639-4234

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