Model-Driven Engineering Ecosystems

Neto, Valdemar Vicente Graciano; Basso, Fábio Paulo; Santos, Rodrigo Pereira dos; Bakar, Noor Hasrina; Kassab, Mohamad; Werner, Cláudia Maria Lima; Oliveira, Toacy C.; Nakagawa, Elisa Yumi

doi:10.1109/sesos/wdes.2019.00016

Cited by 3 publications

(2 citation statements)

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“…In this paper, we propose a reference architecture for evaluating ecosystems of model‐based artifacts, and an implementation of it, named AMINO (A Model reposItory aNalisis framewOrk). AMINO is an analysis framework * able to mine model repositories and to discover and assess the quality of modeling ecosystems therein 12 . We can summarize the scientific contribution of this paper as follows: We outlined and demonstrated the usefulness and the importance of evaluating modeling ecosystems as a whole and not by inspecting the composing artifacts singularly; We identified the requirements that an analytics framework for modeling ecosystems must have, and we assessed the existing tools in the literature covering the requirements; We proposed a reference architecture and a reference implementation fulfilling all the requirements; We combined the discovery and the quality evaluation of modeling ecosystems to extend the quality evaluation to hidden relationships and derived quality aspects that can only be calculated when those two phases are combined. …”

Section: Introductionmentioning

confidence: 99%

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AMINO: A quality assessment framework for modeling ecosystems

Di Ruscio,

Iovino,

Pierantonio

2023

J Software Evolu Process

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SummaryModels are core assets in Model‐Driven Engineering (MDE). They are pervasively used throughout software development processes to leverage automation, increase cost‐effectiveness, and enhance quality factors. Model repositories have been successfully proposed to enforce reuse and elicit correlations among modeling artifacts, enabling storing operations on model‐based artifacts and collaborative modeling features. Maintaining and improving the quality of modeling artifacts is mandatory for software quality scale‐ups. Limiting the exploration of datasets and repositories of models to individual artifacts might reduce the ability to capture insights and reuse opportunities. This paper proposes AMINO, an analytics tool for model repositories supporting the discovery and quality evaluation of modeling ecosystems.

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Section: Introductionmentioning

confidence: 99%

“…AMINO is an analysis framework * able to mine model repositories and to discover and assess the quality of modeling ecosystems therein. 12 We can summarize the scientific contribution of this paper as follows:…”

mentioning

confidence: 99%