Quality assessment of systematic reviews in software engineering

Zhou, You; Zhang, He; Huang, Xin; Yang, Song; Babar, Muhammad Ali; Tang, Hao

doi:10.1145/2745802.2745815

Cited by 52 publications

(38 citation statements)

References 19 publications

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“…The confidence we can place in the results of a systematic review is largely dependent upon the quality of the evidence collected in that review (Dybå and Dingsøyr 2008;Zhou et al 2015). The same holds for a tertiary study, such as this one, where appraising the quality of the secondary studies selected for our review is extremely relevant.…”

Section: Quality Assessmentmentioning

confidence: 99%

Quality in model-driven engineering: a tertiary study

2016

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Model-driven engineering (MDE) is believed to have a significant impact in software quality. However, researchers and practitioners may have a hard time locating consolidated evidence on this impact, as the available information is scattered in several different publications. Our goal is to aggregate consolidated findings on quality in MDE, facilitating the work of researchers and practitioners in learning about the coverage and main findings of existing work as well as identifying relatively unexplored niches of research that need further attention. We performed a tertiary study on quality in MDE, in order to gain a better understanding of its most prominent findings and existing challenges, as reported in the literature. We identified 22 systematic literature reviews and mapping studies and the most relevant quality attributes addressed by each of those studies, in the context of MDE. Maintainability is clearly the most often studied and reported quality attribute impacted by MDE. Eighty out of 83 research questions in the selected secondary studies have a structure that is more often associated with mapping existing research than with answering more concrete research questions (e.g., comparing two alternative MDE approaches with respect to their impact on a specific quality attribute). We briefly outline the main contributions of each of the selected literature reviews. In the collected studies, we observed a broad coverage of software product quality, although frequently accompanied by notes on how much more empirical research is needed to further validate existing claims. Relatively, little attention seems to be devoted to the impact of MDE on the quality in use of products developed using MDE.

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Section: Quality Assessmentmentioning

confidence: 99%

Quality in model-driven engineering: a tertiary study

2016

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“…Quality assessment (QA) is a process of assessing the quality of the selected sources based on the inclusion and exclusion criteria (Al-Emran, Mezhuyev, & Kamaludin, 2018), and it is created as supporting evidence for the SLR (Zhou et al, 2015). Table 3 describes the QA checklist in this paper adapted from Zhou et al (2015). Does the selected source have well-defined metrics such as research method, research design, and measures applied in the study?…”

Section: Quality Assessmentmentioning

confidence: 99%

“…Table 4 illustrates the QA metrics for scoring the quality of the collected sources based on the QA checklist (see Table 3) in this research. The QA metric was developed by applying a checklist approach suggested by Zhou et al (2015). The QA metrics analyse the sources and re-assess the inclusion and exclusion criteria to ensure the selection process is accurate, and to remove sources that do not meet the requirements.…”

Section: Quality Assessmentmentioning

confidence: 99%

Conceptualising Capabilities and Value Co-Creation in a Digital Business Ecosystem (DBE): A Systematic Literature Review

Tan

Sunil²,

Binita

2020

J INFORM SYSTEMS ENG

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“…Searching the fields of title, keyword and abstract of the publications performed the search. We reused using the following search string from previous work [5], and checked the result.…”

Section: )mentioning

confidence: 99%

A Map of Threats to Validity of Systematic Literature Reviews in Software Engineering

Zhou

Yu-qin²,

Zhang

et al. 2016

2016 23rd Asia-Pacific Software Engineering Conference (APSEC)

Self Cite

174

127

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Context: The assessment of Threats to Validity (TTVs) is critical to secure the quality of empirical studies in Software Engineering (SE). In the recent decade, Systematic Literature Review (SLR) was becoming an increasingly important empirical research method in SE. One of the mechanisms of insuring the level of scientific value in the findings of an SLR is to rigorously assess its validity. Hence, it is necessary to realize the status quo and issues of TTVs of SLRs in SE. Objective: This study aims to investigate thestate-of-the-practice of TTVs of the SLRs published in SE, and further support SE researchers to improve the assessment and strategies against TTVs in order to increase the quality of SLRs in SE. Method: We conducted a tertiary study by reviewing the SLRs in SE that report the assessment of TTVs. Results: We identified 316 SLRs published from 2004 to the first half of 2015, in which TTVs are discussed. The issues associated to TTVs were also summarized and categorized. Conclusion: The common TTVs related to SLR research, such as internal validity and reliability, were thoroughly discussed in most SLRs. The threats to construct validity and external validity drew less attention. Moreover, there are few strategies and tactics being reported to cope with the various TTVs.

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Quality assessment of systematic reviews in software engineering

Cited by 52 publications

References 19 publications

Quality in model-driven engineering: a tertiary study

Quality in model-driven engineering: a tertiary study

Conceptualising Capabilities and Value Co-Creation in a Digital Business Ecosystem (DBE): A Systematic Literature Review

A Map of Threats to Validity of Systematic Literature Reviews in Software Engineering

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