Multivocal literature reviews in software engineering: Preliminary findings from a tertiary study

Neto, Geraldo Torres G.; Santos, Wylliams Barbosa; Endo, Patrícia Takako; Fagundes, A. A. Roberta

doi:10.1109/esem.2019.8870142

Cited by 11 publications

(17 citation statements)

References 16 publications

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“…The decision to cover 'grey' literature in this research was motivated as follows. As proposed in number of information systems and software engineering domain publications (Garousi, Felderer & Mäntylä, 2019;Neto et al, 2019), SLR as stand-alone method may not provide sufficient insight into 'state of practice'. It was also identified (Garousi, Felderer & Mäntylä, 2016) that 'grey' literature can give substantial benefits in certain areas of software engineering, in particular, when the topic of research is related to industrial and practical settings.…”

Section: Primary Searchmentioning

confidence: 99%

“…Thus, both databases complement each other. The selected non-indexed database source for 'grey' literature is Google Scholar, as it is comprehensive source of both academic and 'grey' literature publications and referred as such extensively (Garousi, Felderer & Mäntylä, 2019;Neto et al, 2019).…”

Section: Primary Searchmentioning

confidence: 99%

“…In our study we restricted ourselves to the 1st tier 'grey' literature publications of the limited number of 'grey' literature producers. In particular, from the list of producers (Neto et al, 2019) we have adopted and focused on government departments and agencies, non-profit economic, trade organizations ('thinktanks') and professional associations, academic and research institutions, businesses and corporations (consultancy companies and established private companies). The 1st tier 'grey' literature selected items include: (1) government, academic, and private sector consultancy reports 2 , (2) theses (not lower than Master level) and PhD Dissertations, (3) research reports, (4) working papers, (5) conference proceedings, preprints.…”

Section: Primary Searchmentioning

confidence: 99%

“…The 1st tier 'grey' literature selected items include: (1) government, academic, and private sector consultancy reports 2 , (2) theses (not lower than Master level) and PhD Dissertations, (3) research reports, (4) working papers, (5) conference proceedings, preprints. With inclusion of the 1st tier 'grey' literature criteria we mitigate quality assessment challenge especially relevant and reported for it (Garousi, Felderer & Mäntylä, 2019;Neto et al, 2019).…”

Section: Primary Searchmentioning

confidence: 99%

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Adaptations of data mining methodologies: a systematic literature review

Plotnikova¹,

Dumas²,

Milani³

2020

PeerJ Computer Science

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The use of end-to-end data mining methodologies such as CRISP-DM, KDD process, and SEMMA has grown substantially over the past decade. However, little is known as to how these methodologies are used in practice. In particular, the question of whether data mining methodologies are used ‘as-is’ or adapted for specific purposes, has not been thoroughly investigated. This article addresses this gap via a systematic literature review focused on the context in which data mining methodologies are used and the adaptations they undergo. The literature review covers 207 peer-reviewed and ‘grey’ publications. We find that data mining methodologies are primarily applied ‘as-is’. At the same time, we also identify various adaptations of data mining methodologies and we note that their number is growing rapidly. The dominant adaptations pattern is related to methodology adjustments at a granular level (modifications) followed by extensions of existing methodologies with additional elements. Further, we identify two recurrent purposes for adaptation: (1) adaptations to handle Big Data technologies, tools and environments (technological adaptations); and (2) adaptations for context-awareness and for integrating data mining solutions into business processes and IT systems (organizational adaptations). The study suggests that standard data mining methodologies do not pay sufficient attention to deployment issues, which play a prominent role when turning data mining models into software products that are integrated into the IT architectures and business processes of organizations. We conclude that refinements of existing methodologies aimed at combining data, technological, and organizational aspects, could help to mitigate these gaps.

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Section: Primary Searchmentioning

confidence: 99%

Section: Primary Searchmentioning

confidence: 99%

Section: Primary Searchmentioning

confidence: 99%

Section: Primary Searchmentioning

confidence: 99%

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Adaptations of data mining methodologies: a systematic literature review

Plotnikova¹,

Dumas²,

Milani³

2020

PeerJ Computer Science

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“…O uso da LC em pesquisas acadêmicas no campo de Engenharia de Software (ES) vem se mostrando relevante. Nos últimos anos, estudos envolvendo LC vêm atraindo atenção de pesquisadores do campo de ES [Neto et al 2019].…”

Section: A Literatura Cinza Na Engenharia De Softwareunclassified

Ferramenta de Web-Scraping: Impactos da COVID-19 na Indústria de Software

Souza

Filho

Santos

2021

Anais Estendidos Do XVII Simpósio Brasileiro De Sistemas De Informação (Anais Estendidos Do SBSI 2021)

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A pandemia causada pelo COVID-19 traz desafios para a indústria de software. Para o estudo deste contexto, a utilização da Literatura Cinza é de grande relevância. No entanto, há uma lacuna no que diz respeito a ferramentas de busca para tal conteúdo. Esse trabalho apresenta informações acerca de uma ferramenta de Web Scraping, desenvolvida para busca de Literatura Cinza no contexto de desenvolvimento ágil de software. Utilizamos o método de Design Science e mostramos resultados preliminares compostos por mais de 7900 documentos capturados pela ferramenta, a qual deve ser aprimorada futuramente e já se mostra útil no meio acadêmico.

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Industry practices and challenges for the evolvability assurance of microservices

et al. 2021

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Context Microservices as a lightweight and decentralized architectural style with fine-grained services promise several beneficial characteristics for sustainable long-term software evolution. Success stories from early adopters like Netflix, Amazon, or Spotify have demonstrated that it is possible to achieve a high degree of flexibility and evolvability with these systems. However, the described advantageous characteristics offer no concrete guidance and little is known about evolvability assurance processes for microservices in industry as well as challenges in this area. Insights into the current state of practice are a very important prerequisite for relevant research in this field. Objective We therefore wanted to explore how practitioners structure the evolvability assurance processes for microservices, what tools, metrics, and patterns they use, and what challenges they perceive for the evolvability of their systems. Method We first conducted 17 semi-structured interviews and discussed 14 different microservice-based systems and their assurance processes with software professionals from 10 companies. Afterwards, we performed a systematic grey literature review (GLR) and used the created interview coding system to analyze 295 practitioner online resources. Results The combined analysis revealed the importance of finding a sensible balance between decentralization and standardization. Guidelines like architectural principles were seen as valuable to ensure a base consistency for evolvability and specialized test automation was a prevalent theme. Source code quality was the primary target for the usage of tools and metrics for our interview participants, while testing tools and productivity metrics were the focus of our GLR resources. In both studies, practitioners did not mention architectural or service-oriented tools and metrics, even though the most crucial challenges like Service Cutting or Microservices Integration were of an architectural nature. Conclusions Practitioners relied on guidelines, standardization, or patterns like Event-Driven Messaging to partially address some reported evolvability challenges. However, specialized techniques, tools, and metrics are needed to support industry with the continuous evaluation of service granularity and dependencies. Future microservices research in the areas of maintenance, evolution, and technical debt should take our findings and the reported industry sentiments into account.

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Multivocal literature reviews in software engineering: Preliminary findings from a tertiary study

Cited by 11 publications

References 16 publications

Adaptations of data mining methodologies: a systematic literature review

Adaptations of data mining methodologies: a systematic literature review

Ferramenta de Web-Scraping: Impactos da COVID-19 na Indústria de Software

Industry practices and challenges for the evolvability assurance of microservices

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