Guidelines for the search strategy to update systematic literature reviews in software engineering

Wohlin, Claes; Mendes, Emilia; Felizardo, Katia Romero; Kalinowski, Marcos

doi:10.1016/j.infsof.2020.106366

Cited by 71 publications

(61 citation statements)

References 29 publications

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“…Given that grey literature and older papers will generally constitute the largest group of relevant papers not yet included, it is more apt to inspect references than citations. Forward snowballing is well suited to updating systematic reviews (Wohlin et al, 2020), but, as we show in Section 4.1.7, SYMBALS can also be used to update a systematic review.…”

Section: Backward Snowballingmentioning

confidence: 99%

SYMBALS: A Systematic Review Methodology Blending Active Learning and Snowballing

Haastrecht

Sarhan

Özkan

et al. 2021

Front. Res. Metr. Anal.

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Research output has grown significantly in recent years, often making it difficult to see the forest for the trees. Systematic reviews are the natural scientific tool to provide clarity in these situations. However, they are protracted processes that require expertise to execute. These are problematic characteristics in a constantly changing environment. To solve these challenges, we introduce an innovative systematic review methodology: SYMBALS. SYMBALS blends the traditional method of backward snowballing with the machine learning method of active learning. We applied our methodology in a case study, demonstrating its ability to swiftly yield broad research coverage. We proved the validity of our method using a replication study, where SYMBALS was shown to accelerate title and abstract screening by a factor of 6. Additionally, four benchmarking experiments demonstrated the ability of our methodology to outperform the state-of-the-art systematic review methodology FAST2.

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Section: Backward Snowballingmentioning

confidence: 99%

SYMBALS: A Systematic Review Methodology Blending Active Learning and Snowballing

Haastrecht

Sarhan

Özkan

et al. 2021

Front. Res. Metr. Anal.

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“…In the third step, following a snowball approach [29], the cited references of the selected studies were analyzed. The same parameters elaborated for the second step were applied.…”

Section: Snowball Inclusionmentioning

confidence: 99%

Application of the Socio-Ecological System Framework to Forest Fire Risk Management: A Systematic Literature Review

et al. 2021

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Although increasing concern about climate change has raised awareness of the fundamental role of forest ecosystems, forests are threatened by human-induced impacts worldwide. Among them, wildfire risk is clearly the result of the interaction between human activities, ecological domains, and climate. However, a clear understanding of these interactions is still needed both at the global and local levels. Numerous studies have proven the validity of the socioecological system (SES) approach in addressing this kind of interdisciplinary issue. Therefore, a systematic review of the existing literature on the application of SES frameworks to forest ecosystems is carried out, with a specific focus on wildfire risk management. The results demonstrate the existence of different methodological approaches that can be grouped into seven main categories, which range from qualitative analysis to quantitative spatially explicit investigations. The strengths and limitations of the approaches are discussed, with a specific reference to the geographical setting of the works. The research suggests the importance of local community involvement and local knowledge consideration in wildfire risk management. This review provides a starting point for future research on forest SES and a supporting tool for the development of a sustainable wildfire risk adaptation and mitigation strategy.

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“…Research roadmaps are intended to point to research needed in an area to make further progress. In the proceedings of the the track Future of Software Engineering at the International Software Engineering Conference (ICSE) in the year 2000, 12 26 roadmaps were published covering software engineering in general and numerous areas within software engineering. Since then, roadmaps are published regularly either updating previous roadmaps 13 or adding new roadmaps 14 due to the evolution of technology and the software engineering discipline as such.…”

Section: Research Roadmapsmentioning

confidence: 99%

“…23 Considering systems built using existing software assets, a recent trend is the emergence of software ecosystems. 24 Manikas 25 and Wohlin et al 26 conducted systematic literature reviews to provide an overview of the state of the area as well as to point to future research directions concerning software ecosystems, including decision-making for software ecosystems. The However, the research directions do not address the use of software assets coming from a software ecosystem, and in particular, the areas concerning decision-making related to developing composite software using software assets from a software ecosystem.…”

Section: Composite Softwarementioning

confidence: 99%

“…The quality of all papers included was assessed on the basis of rigor and relevance by using the guidelines by Ivarsson and Gorschek. 44 The study only identified a small set of papers (26) investigating the choice of component origins. A small subset (nine papers) was of empirical nature, using methods such as surveys, interview studies and case studies.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Towards evidence‐based decision‐making for identification and usage of assets in composite software: A research roadmap

Wohlin

Papatheocharous

Carlson

et al. 2021

J Software Evolu Process

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Software engineering is decision intensive. Evidence-based software engineering is suggested for decision-making concerning the use of methods and technologies when developing software. Software development often includes the reuse of software assets, for example, open-source components. Which components to use have implications on the quality of the software (e.g., maintainability). Thus, research is needed to support decision-making for composite software. This paper presents a roadmap for research required to support evidence-based decision-making for choosing and integrating assets in composite software systems. The roadmap is developed as an output from a 5-year project in the area, including researchers from three different organizations. The roadmap is developed in an iterative process and is based on (1) systematic literature reviews of the area; (2) investigations of the state of practice, including a case survey and a survey; and (3) development and evaluation of solutions for asset identification and selection. The research activities resulted in identifying 11 areas in need of research. The areas are grouped into two categories: areas enabling evidence-based decision-making and those related to supporting the decision-making. The roadmap outlines research needs in these 11 areas. The research challenges and research directions presented in this roadmap are key areas for further research to support evidence-based decision-making for composite software.

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Guidelines for the search strategy to update systematic literature reviews in software engineering

Cited by 71 publications

References 29 publications

SYMBALS: A Systematic Review Methodology Blending Active Learning and Snowballing

SYMBALS: A Systematic Review Methodology Blending Active Learning and Snowballing

Application of the Socio-Ecological System Framework to Forest Fire Risk Management: A Systematic Literature Review

Towards evidence‐based decision‐making for identification and usage of assets in composite software: A research roadmap

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