2018 37th International Conference of the Chilean Computer Science Society (SCCC) 2018
DOI: 10.1109/sccc.2018.8705256
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An Empirical Study of Scalability Frameworks in Open Source Microservices-based Systems

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Cited by 6 publications
(7 citation statements)
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“…Architectural patterns and tactics for MSA: Architectural patterns and tactics represent generic and reuse-driven knowledge that enables developers and architects to rely on best practices during design and development of MSA-based systems [21]. Several studies, such as [19,22], focused on mining software repositories (e.g., analyzing version control, change logs, and design documents)…”
Section: Related Work 21 Mining Knowledge From Open-source Microservices Systemsmentioning
confidence: 99%
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“…Architectural patterns and tactics for MSA: Architectural patterns and tactics represent generic and reuse-driven knowledge that enables developers and architects to rely on best practices during design and development of MSA-based systems [21]. Several studies, such as [19,22], focused on mining software repositories (e.g., analyzing version control, change logs, and design documents)…”
Section: Related Work 21 Mining Knowledge From Open-source Microservices Systemsmentioning
confidence: 99%
“…The postmortem analysis of repositories such as GitHub or logs of source code supports the empirical discovery of patterns to address various reuse-driven development [19,21] and evolution issues [1] of MSAs. Specifically, the studies [19,21] investigated artifacts of MSA-based projects deployed on GitHub, such as developers' discussion and source code files, to discover 17 architectural patterns that address reusability [19] and 5 architectural tactics that resolve scalability issues of open-source MSAbased systems. In contrast to the design and development phase, the study in [1] investigated the modernization processes of legacy software to discover and document 15 patterns for architecture-centric refactoring and migration of MSA-based systems.…”
Section: Related Work 21 Mining Knowledge From Open-source Microservices Systemsmentioning
confidence: 99%
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