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Regression testing for large-scale embedded software development: Exploring the state of practice
Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.ORCID iD: 0000-0001-8177-4355
Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.ORCID iD: 0000-0002-1532-8223
Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.ORCID iD: 0000-0003-0639-4234
Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.ORCID iD: 0000-0003-3567-9300
2020 (English)In: Information and Software Technology, ISSN 0950-5849, E-ISSN 1873-6025, Vol. 120, article id UNSP 106254Article in journal (Refereed) Published
Abstract [en]

Context: A majority of the regression testing techniques proposed by the research have not been adopted in industry. To increase adoption rates, we need to better understand the practitioners' perspectives on regression testing.

Objective: This study aims at exploring the regression testing state of practice in the large-scale embedded software development. The study has two objectives, 1) to highlight the potential challenges in practice, and 2) to identify the industry-relevant research areas regarding regression testing.

Method: We conducted a qualitative study in two large-scale embedded software development companies, where we carried out semi-structured interviews with representatives from five software testing teams. We did conduct the detailed review of the process documentation of the companies to complement/validate the findings of the interviews.

Results: Mostly, the practitioners run regression testing with a selected scope, the selection of scope depends upon the size, complexity, and location of the change. Test cases are prioritized on the basis of risk and critical functionality. The practitioners rely on their knowledge and experience for the decision making regarding selection and prioritization of test cases.The companies are using both automated and manual regression testing, and mainly they rely on in-house developed tools for test automation. The challenges identified in the companies are: time to test, information management, test suite maintenance, lack of communication, test selection/prioritization, lack of assessment, etc. The proposed improvements are in line with the identified challenges. Regression testing goals identified in this study are customer satisfaction, critical defect detection, confidence, effectiveness, efficiency, and controlled slip through of faults.

Conclusions: Considering the current state of practice and identified challenges we conclude that there is a need to reconsider the regression test strategy in the companies. Researchers need to analyze the industry perspective while proposing new regression testing techniques. The industry-academia collaboration projects would be a good platform in this regard.

Place, publisher, year, edition, pages
Elsevier, 2020. Vol. 120, article id UNSP 106254
Keywords [en]
Regression testing, practices, challenges, goals, multi-case study
National Category
Software Engineering
Identifiers
URN: urn:nbn:se:bth-17362DOI: 10.1016/j.infsof.2019.106254ISI: 000514233800006OAI: oai:DiVA.org:bth-17362DiVA, id: diva2:1267005
Projects
EASE - Embedded Applications Software Engineering
Part of project
SERT- Software Engineering ReThought, Knowledge Foundation
Funder
Vinnova, 2015-03235Available from: 2018-11-30 Created: 2018-11-30 Last updated: 2022-09-18Bibliographically approved
In thesis
1. Regression Testing Challenges and Solutions: An Industry-Academia Perspective
Open this publication in new window or tab >>Regression Testing Challenges and Solutions: An Industry-Academia Perspective
2019 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Background: Software quality assurance (QA) is an essential activity in the software development lifecycle. Among the different QA activities, regression testing is a challenging task for large-scale software development. Regression testing is a well-researched area, and a large number of techniques have been proposed to fulfill the needs of industry. Despite the extensive research, the adoption of proposed regression testing techniques in the industry is limited. Studies show that there is a visible gap between research and practice.

Objective: This work aims at reducing the gap between industry and academia in regression testing. To fulfill this aim we have the following objectives:

1) Understanding the practitioners' goals regarding regression testing.

2) Understanding the current state of regression testing practice and challenges in the industry.

3) Investigating the testing research applicable in an industrial context.

Method: We conducted multiple studies using different methods.

To explore the industry perspective on regression testing we used focus group and interview-based studies. To explore solutions from the literature, we used the systematic literature review and systematic mapping study.

Results: This thesis presents the practitioners' specific regression testing goals. The identified goals are confidence, controlled fault slippage, effectiveness, efficiency, and customer satisfaction. The challenges identified in the thesis are of two categories, 1) management related challenges and 2) technical challenges. Technical challenges relate to test suite maintenance, test case selection, test case prioritization, evaluation of regression testing.

We have mapped 26 empirically evaluated regression testing techniques to the context, effect, and information taxonomies, and provided a guide to the practitioners regarding the adoption of the techniques in an industrial setting. We have also classified 56 model-based test case generation techniques regarding their strengths/limitations, input/intermediate models used, and relevance to the industrial context.

Conclusions: The challenges identified in this study are not new for research and practice. There could be two reasons regarding the presence of recurring challenges: 1) regression testing techniques proposed in the literature do not fit the companies’ context, 2) or, companies are not aware of the availability of the techniques that could be suitable for their context. To support the adoption of existing research on regression testing in the industry, we have presented three taxonomies. These taxonomies, allow the characterization of regression testing techniques and enable to determine which of these techniques might be suitable in a given context. Furthermore, the identification of information needs for these techniques would be helpful to learn the implications regarding the cost of adoption. Regarding the support in test case generation, we conclude that current research on interaction model-based test case generation techniques did not illustrate the use of rigorous methodology, and currently, model-based test case generation techniques have low relevance for the industrial problems.

Place, publisher, year, edition, pages
Karlskrona, Sweden: Blekinge Tekniska Högskola, 2019. p. 146
Series
Blekinge Institute of Technology Licentiate Dissertation Series, ISSN 1650-2140 ; 2
National Category
Software Engineering
Identifiers
urn:nbn:se:bth-17381 (URN)978-91-7295-365-9 (ISBN)
Presentation
2019-01-08, J1650, Campus Gräsvik, Karlskrona, 14:00 (English)
Opponent
Supervisors
Funder
VINNOVA, 2015-03235
Available from: 2018-12-06 Created: 2018-12-05 Last updated: 2019-01-17Bibliographically approved
2. Understanding and improving regression testing practice
Open this publication in new window or tab >>Understanding and improving regression testing practice
2022 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Background

Regression testing is a complex and challenging activity and consumes a significant portion of software maintenance costs. Researchers are proposing various techniques to deal with the cost and complexity of regression testing. Yet, practitioners face various challenges when planning and executing regression testing. One of the main reasons is the disparity between research and practice perspectives on the goals and challenges of regression testing. In addition, it is difficult for practitioners to find techniques relevant to their context, needs, and goals because most proposed techniques lack contextual information.

Objective

This work aims to understand the challenges to regression testing practice and find ways to improve it. To fulfil this aim, we have the following objectives:

1) understanding the current state of regression testing practice, goals, and challenges,

2) finding ways to utilize regression testing research in practice, and

3) providing support in structuring and improving regression testing practice. 

Method

We have utilized various research methods, including literature reviews, workshops, focus groups, case studies, surveys, and experiments, to conduct the studies for this thesis.

Results

Research and practice stress different goals, and both follow their priorities. Researchers propose new regression testing techniques to increase the test suite's fault detection rate and maximise coverage. The practitioners consider test suite maintenance, controlled fault slippage, and confidence their priority goals. The practitioners rely on expert judgment instead of a well-defined regression testing process. They face various challenges in regression testing, such as time to test, test suit maintenance, lack of communication, lack of strategy, lack of assessment, and issues in test case selection and prioritization. 

We have proposed a GQM model representing research and practice perspectives on regression testing goals. The proposed model can help reduce disparities in research and practice perspectives and cope with the lack of assessment. 

We have created regression testing taxonomies to guide practitioners in finding techniques suitable to their product context, goals, and needs.  Further, based on the experiences of replicating a regression testing technique, we have provided guidelines for future replications and adoption of regression testing techniques.

Finally, we have designed regression testing checklists to support practitioners in decision-making while planning and performing regression testing. Practitioners who evaluated the checklists reported that the checklists covered essential aspects of regression testing and were useful and customizable to their context.

Conclusions

The thesis points out the gap in research and practice perspectives of regression testing. The regression testing challenges identified in this thesis are the evidence that either research does not consider these challenges or practitioners are unaware of how to replicate the regression testing research into their context. The GQM model presented in this thesis is a step toward reducing the research and practice gap in regression testing. Furthermore, the taxonomies and the replication experiment provide a way forward to adopting regression testing research. Finally, the checklists proposed in this thesis could help improve communication and regression test strategy. Moreover, the checklists will provide a basis for structuring and improving regression testing practice.

Place, publisher, year, edition, pages
Karlskrona: Blekinge Tekniska Högskola, 2022. p. 297
Series
Blekinge Institute of Technology Doctoral Dissertation Series, ISSN 1653-2090 ; 7
Keywords
Regression testing, Goals, GQM, Replication, Checklists
National Category
Software Engineering
Research subject
Software Engineering
Identifiers
urn:nbn:se:bth-23634 (URN)978-91-7295-444-1 (ISBN)
Public defence
2022-10-31, C413A, Campus Grasvik, Karlskrona, 13:00 (English)
Opponent
Supervisors
Available from: 2022-09-20 Created: 2022-09-18 Last updated: 2022-10-10Bibliographically approved

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Minhas, Nasir MehmoodPetersen, KaiBörstler, JürgenWnuk, Krzysztof

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