A Customizable Approach for the Automated Quality Assessment of Modelling Artifacts

Basciani, Francesco; Rocco, Juri Di; Ruscio, Davide Di; Iovino, Ludovico; Pierantonio, Alfonso

doi:10.1109/quatic.2016.025

Cited by 17 publications

(29 citation statements)

References 9 publications

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“…The MicroQuality approach has been designed specifically for microservice-based systems. It combines the advantages of the approach for recovering microservice-based systems presented in [14] with the advantages of the extensible and generic approach assessing the quality of modelling artefacts published by Basciani et al [3]. On the one hand, a limitation of the scope of our approach to MSA lies in the fact that the used recovery approach relies on specific sources of information (e.g., Docker files) typically available only in microservice-based systems.…”

Section: Discussionmentioning

confidence: 99%

“…The architecture model represents the architecture of the system which is composed by all the elements of the microservices architecture. Its Figure 4: The customized quality metamodel from [3] representation is based on a domain-specific language (DSL) for microservice-based systems, that we reused in our approach. We briefly recall its underlying metamodel with the intent of presenting an example of an MSA Model.…”

Section: Modeling Microservice Architecturesmentioning

confidence: 99%

“…Another important component of MicroQuality is the integration of the Quality Metamodel presented by Basciani et al [3], that we customized for representing quality definition in the field of MSA. This approach plays a key role since it enables the specification of quality models according to user requirements for different software artefacts and domains, like MSA.…”

Section: Defining Quality Attributes For Microservice Architecturesmentioning

confidence: 99%

“…A MetricProvider is labelled with the attribute id, used to identify and retrieve the actual software component implementing the considered metric, that is part of the overall architecture of the proposed approach, labeled with E in Figure 2. This metamodel has been extended in order to enable the evaluation of internal elements and not only an overall evaluation as proposed in [3]. This has been enabled with the attribute type inside MetricProvider metaclass, allowing to associate the model element to be considered by the metric calculation.…”

Section: Defining Quality Attributes For Microservice Architecturesmentioning

confidence: 99%

“…First of all, our approach specifically targets the domain of microservice-based systems. Second, it combines together (and extends) two different existing approaches: the architecture recovery approach presented by Granchelli et al in [15] and the automated quality assessment approach proposed by Basciani et al in [3]. To the best of our knowledge this is the first approach that provides the possibility to: (i) automatically extract a model of the architecture of a microservice-based system, (ii) support the customization of the quality attributes of the system, and (ii) produce quantitative measures for their assessments.…”

Section: Related Workmentioning

confidence: 99%

See 4 more Smart Citations

An extensible data-driven approach for evaluating the quality of microservice architectures

Cardarelli

Iovino

Francesco

et al. 2019

Proceedings of the 34th ACM/SIGAPP Symposium on Applied Computing

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Microservice architecture (MSA) is defined as an architectural style where the software system is developed as a suite of small services, each running in its own process and communicating with lightweight mechanisms. The benefits of MSA are many, ranging from an increase in development productivity, to better business-IT alignment, agility, scalability, and technology flexibility. The high degree of microservices distribution and decoupling is, however, imposing a number of relevant challenges from an architectural perspective. In this context, measuring, controlling, and keeping a satisfactory level of quality of the system architecture is of paramount importance.In this paper we propose an approach for the specification, aggregation, and evaluation of software quality attributes for the architecture of microservice-based systems. The proposed approach allows developers to (i) produce architecture models of the system, either manually or automatically via recovering techniques, (ii) contribute to an ecosystem of well-specified and automatically-computable software quality attributes for MSAs, and (iii) continuously measure and evaluate the architecture of their systems by (re-)using the software quality attributes defined in the ecosystem. The approach is implemented by using Model-Driven Engineering techniques.The current implementation of the approach has been validated by assessing the maintainability of a third-party, publicly available benchmark system.

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Section: Discussionmentioning

confidence: 99%

Section: Modeling Microservice Architecturesmentioning

confidence: 99%

Section: Defining Quality Attributes For Microservice Architecturesmentioning

confidence: 99%

Section: Defining Quality Attributes For Microservice Architecturesmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 3 more Smart Citations

An extensible data-driven approach for evaluating the quality of microservice architectures

Cardarelli

Iovino

Francesco

et al. 2019

Proceedings of the 34th ACM/SIGAPP Symposium on Applied Computing

Self Cite

View full text Add to dashboard Cite

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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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Discovery the Quality of UML Models Through an Exploration of Dataset in Practice

Doan

Nguyen

Tran

2022

Intelligence of Things: Technologies and Applications

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A Customizable Approach for the Automated Quality Assessment of Modelling Artifacts

Cited by 17 publications

References 9 publications

An extensible data-driven approach for evaluating the quality of microservice architectures

An extensible data-driven approach for evaluating the quality of microservice architectures

AMINO: A quality assessment framework for modeling ecosystems

Discovery the Quality of UML Models Through an Exploration of Dataset in Practice

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