Identification of SLR tool needs – results of a community workshop

Hassler, Edgar; Carver, Jeffrey C.; Hale, David P.; Al-Zubidy, Ahmed

doi:10.1016/j.infsof.2015.10.011

Cited by 32 publications

(26 citation statements)

References 15 publications

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“…Knowledge intensiveness, tediousness and errorproneness are the key factors cited for low adoption of SR in SE. Several tertiary reviews [24,1,7,8,10] are congruent with these observations.…”

Section: Introductionsupporting

confidence: 52%

“…The commonly cited issues are: (i) SR guidelines are time consuming and errorprone [16], (ii) lack of guideline for conducting individual review process steps [17], for example, the guidance on how to eliminate bias [14] from a literature corpus or how to justify the quality of a review outcome, etc. (iii) and lack of guidance to adopt a specific SR technique, i.e., when to prefer SMS over SLR or vice versa [10]. Moreover, software researchers have expressed their difficulties to manage and correlate large number of review artefacts those are produced in the various phases of SR.…”

Section: Doi: 101145/1235mentioning

confidence: 99%

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A Model-Based Approach to Systematic Review of Research Literature

Barat

Clark

Barn

et al. 2017

Proceedings of the 10th Innovations in Software Engineering Conference

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A systematic approach to develop a literature review is attractive because it aims to achieve a repeatable, unbiased and evidence-based outcome. However the existing form of systematic reviews such as Systematic Literature Review (SLR) and Systematic Mapping Study (SMS) are known to be an effort, time, and intellectual intensive endeavour. To address these issues, this paper proposes a model-based approach to Systematic Review (SR) production. The approach uses a domain-specific language expressed as a metamodel to represent research literature, a meta-model to specify SR constructs in a uniform manner, and an associated development process all of which can benefit from computerbased support. The meta-models and process are validated using real-life case study. We claim that the use of metamodeling and model synthesis lead to a reduction in time, effort and the current dependence on human expertise.

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Section: Introductionsupporting

confidence: 52%

Section: Doi: 101145/1235mentioning

confidence: 99%

A Model-Based Approach to Systematic Review of Research Literature

Barat

Clark

Barn

et al. 2017

Proceedings of the 10th Innovations in Software Engineering Conference

View full text Add to dashboard Cite

show abstract

“…These features were chosen in part based on previous studies on user preferences for systematic review software functionality [24,25]. Developers were contacted when insufficient information was available online or in publications about a software package.…”

Section: Review Of Existing Online Toolsmentioning

confidence: 99%

Online tools supporting the conduct and reporting of systematic reviews and systematic maps: a case study on CADIMA and review of existing tools

et al. 2018

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Systematic reviews and systematic maps represent powerful tools to identify, collect, evaluate and summarise primary research pertinent to a specific research question or topic in a highly standardised and reproducible manner. Even though they are seen as the "gold standard" when synthesising primary research, systematic reviews and maps are typically resource-intensive and complex activities. Thus, managing the conduct and reporting of such reviews can become a time consuming and challenging task. This paper introduces the open access online tool CADIMA, which was developed through a collaboration between the Julius Kühn-Institut and the Collaboration for Environmental Evidence, in order to increase the efficiency of the evidence synthesis process and facilitate reporting of all activities to maximise methodological rigour. Furthermore, we analyse how CADIMA compares with other available tools by providing a comprehensive summary of existing software designed for the purposes of systematic review management. We show that CADIMA is the only available open access tool that is designed to: (1) assist throughout the systematic review/map process; (2) be suited to reviews broader than medical sciences; (3) allow for offline data extraction; and, (4) support working as a review team.

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“…The results identified search & study selection as the most desirable feature. Our work addresses the needs identified by both Marshall et al [30] and Hassler et al [19].…”

Section: Related Workmentioning

confidence: 76%

“…Among the results, data extraction and automated analysis emerge as top requirements for reducing the workload. In a similar vein, Hassler et al [19] followed by Al-Zubidy et al [1] consulted Software Engineering researchers conducting SRs to identify and prioritize the necessary SR tool features. The results identified search & study selection as the most desirable feature.…”

Section: Related Workmentioning

confidence: 99%

Reducing the effort for systematic reviews in software engineering

Osborne

Muccini

Lago

et al. 2019

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Context. Systematic Reviews (SRs) are means for collecting and synthesizing evidence from the identification and analysis of relevant studies from multiple sources. To this aim, they use a well-defined methodology meant to mitigate the risks of biases and ensure repeatability for later updates. SRs, however, involve significant effort. Goal. The goal of this paper is to introduce a novel methodology that reduces the amount of manual tedious tasks involved in SRs while taking advantage of the value provided by human expertise. Method. Starting from current methodologies for SRs, we replaced the steps of keywording and data extraction with an automatic methodology for generating a domain ontology and classifying the primary studies. This methodology has been applied in the Software Engineering sub-area of Software Architecture and evaluated by human annotators. Results. The result is a novel Expert-Driven Automatic Methodology, EDAM, for assisting researchers in performing SRs. EDAM combines ontology-learning techniques and semantic technologies with the human-in-the-loop. The first (thanks to automation) fosters scalability, objectivity, reproducibility and granularity of the studies; the second allows tailoring to the specific focus of the study at hand and knowledge reuse from domain experts. We evaluated EDAM on the field of Software Architecture against six senior researchers. As a result, we found that the performance of the senior researchers in classifying papers was not statistically significantly different from EDAM. Conclusions. Thanks to automation of the less-creative steps in SRs, our methodology allows researchers to skip the tedious tasks of keywording and manually classifying primary studies, thus freeing effort for the analysis and the discussion.

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Identification of SLR tool needs – results of a community workshop

Cited by 32 publications

References 15 publications

A Model-Based Approach to Systematic Review of Research Literature

A Model-Based Approach to Systematic Review of Research Literature

Online tools supporting the conduct and reporting of systematic reviews and systematic maps: a case study on CADIMA and review of existing tools

Reducing the effort for systematic reviews in software engineering

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