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Regression testing goals: View of practitioners and researchers
Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för programvaruteknik.ORCID-id: 0000-0001-8177-4355
Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för programvaruteknik.
Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för programvaruteknik.ORCID-id: 0000-0001-7266-5632
Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för programvaruteknik.
2017 (engelsk)Inngår i: 24th Asia-Pacific Software Engineering Conference Workshops (APSECW), IEEE, 2017, s. 25-32Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Context: Regression testing is a well-researched area. However, the majority regression testing techniques proposed by the researchers are not getting the attention of the practitioners. Communication gaps between industry and academia and disparity in the regression testing goals are the main reasons. Close collaboration can help in bridging the communication gaps and resolving the disparities.Objective: The study aims at exploring the views of academics and practitioners about the goals of regression testing. The purpose is to investigate the commonalities and differences in their viewpoints and defining some common goals for the success of regression testing.Method: We conducted a focus group study, with 7 testing experts from industry and academia. 4 testing practitioners from 2companies and 3 researchers from 2 universities participated in the study. We followed GQM approach, to elicit the regression testing goals, information needs, and measures.Results: 43 regression testing goals were identified by the participants, which were reduced to 10 on the basis of similarity among the identified goals. Later during the priority assignment process, 5 goals were discarded, because the priority assigned to these goals was very low. Participants identified 47 information needs/questions required to evaluate the success of regression testing with reference to goal G5 (confidence). Which were then reduced to10 on the basis of similarity. Finally, we identified measures to gauge those information needs/questions, which were corresponding to the goal (G5).Conclusions: We observed that participation level of practitioners and researchers during the elicitation of goals and questions was same. We found a certain level of agreement between the participants regarding the regression testing definitions and goals.But there was some level of disagreement regarding the priorities of the goals. We also identified the need to implement a regression testing evaluation framework in the participating companies.

sted, utgiver, år, opplag, sider
IEEE, 2017. s. 25-32
Emneord [en]
Regression testing, Regression testing goals, GQM, Focus group
HSV kategori
Identifikatorer
URN: urn:nbn:se:bth-16009DOI: 10.1109/APSECW.2017.23ISI: 000428319200008ISBN: 978-1-5386-2649-8 (digital)OAI: oai:DiVA.org:bth-16009DiVA, id: diva2:1192426
Konferanse
24th Asia-Pacific Software Engineering Conference, Nanjing
Prosjekter
EASE (Embedded Applications Software Engineering, ease.cs.lth.se)Tilgjengelig fra: 2018-03-22 Laget: 2018-03-22 Sist oppdatert: 2018-12-05bibliografisk kontrollert
Inngår i avhandling
1. Regression Testing Challenges and Solutions: An Industry-Academia Perspective
Åpne denne publikasjonen i ny fane eller vindu >>Regression Testing Challenges and Solutions: An Industry-Academia Perspective
2019 (engelsk)Licentiatavhandling, med artikler (Annet vitenskapelig)
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.

sted, utgiver, år, opplag, sider
Karlskrona, Sweden: Blekinge Tekniska Högskola, 2019. s. 146
Serie
Blekinge Institute of Technology Licentiate Dissertation Series, ISSN 1650-2140 ; 2
HSV kategori
Identifikatorer
urn:nbn:se:bth-17381 (URN)978-91-7295-365-9 (ISBN)
Presentation
2019-01-08, J1650, Campus Gräsvik, Karlskrona, 14:00 (engelsk)
Opponent
Veileder
Forskningsfinansiär
VINNOVA, 2015-03235
Tilgjengelig fra: 2018-12-06 Laget: 2018-12-05 Sist oppdatert: 2019-01-17bibliografisk kontrollert

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