Towards Micro Service Architecture Recovery: An Empirical Study

Alshuqayran, Nuha; Alí, Nour; Evans, Roger

doi:10.1109/icsa.2018.00014

Cited by 44 publications

(45 citation statements)

References 13 publications

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“…Some studies mainly focus on modeling microservices. 205,206 Their focus partially overlaps with our following research question: what are the modeling approaches used to define the granularity of a microservice?…”

Section: Related Studiesmentioning

confidence: 99%

Microservice transition and its granularity problem: A systematic mapping study

Hassan¹,

Bahsoon²,

Kazman

2020

Softw Pract Exp

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Microservices have gained wide recognition and acceptance in software industries as an emerging architectural style for autonomic, scalable, and more reliable computing. The transition to microservices has been highly motivated by the need for better alignment of technical design decisions with improving value potentials of architectures. Despite microservices' popularity, research still lacks disciplined understanding of transition and consensus on the principles and activities underlying that transition. In this paper, we report on a systematic mapping study that consolidates various views, approaches and activities that commonly assist in the transition to microservices. The study aims to provide a better understanding of the transition; it also contributes a working definition of the transition and technical activities underlying it. We term the transition and technical activities leading to microservice architectures as microservitization. We then shed light on a fundamental problem of microservitization: microservice granularity and reasoning about its adaptation as first-class entities. This study reviews state-of-the-art and-practice related to reasoning about microservice granularity; it reviews modeling approaches, aspects considered, guidelines and processes used to reason about microservice granularity. This study identifies opportunities for future research and development related to reasoning about microservice granularity.

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Section: Related Studiesmentioning

confidence: 99%

Microservice transition and its granularity problem: A systematic mapping study

Hassan¹,

Bahsoon²,

Kazman

2020

Softw Pract Exp

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“…Using deployment artifacts for containers, particularly Docker Compose files and build scripts, support identifying the architecture of a microservice system [134]. It can identify remote endpoints and services and dependencies.…”

Section: Deployment / Build Configuration Analysismentioning

confidence: 99%

On Code Analysis Opportunities and Challenges for Enterprise Systems and Microservices

et al. 2020

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Code analysis brings excellent benefits to software development, maintenance, and quality assurance. Various tools can uncover code defects or even software bugs in a range of seconds. For many projects and developers, the code analysis tools became essential in their daily routines. However, how can code analysis help in an enterprise environment? Enterprise software solutions grow in scale and complexity. These solutions no longer involve only plain objects and basic language constructs but operate with various components and mechanisms simplifying the development of such systems. Enterprise software vendors have adopted various development and design standards; however, there is a gap between what constructs the enterprise frameworks use and what current code analysis tools recognize. This manuscript aims to challenge the mainstream research directions of code analysis and motivate for a transition towards code analysis of enterprise systems with interesting problems and opportunities. In particular, this manuscript addresses selected enterprise problems apparent for monolithic and distributed enterprise solutions. It also considers challenges related to the recent architectural push towards a microservice architecture. Along with open-source proof-of-concept prototypes to some of the challenges, this manuscript elaborates on code analysis directions and their categorization. Furthermore, it suggests one possible perspective of the problem area using aspect-oriented programming.

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“…Two secondary studies [1,8] have reported a possible lack of research in architecture recovery techniques specific for MSA. Two different approaches have been published so far: MicroART [15] and MiSAR [2]. MicroART is an approach for automatic architecture recovery of MSA systems and leverages its own specific domain-specific language using Model Driven Engineering techniques.…”

Section: Related Workmentioning

confidence: 99%

“…MicroART is an approach for automatic architecture recovery of MSA systems and leverages its own specific domain-specific language using Model Driven Engineering techniques. MiSAR [2] is a more recent approach for architecture recovery and relies on a different set of concepts mapped on its own specific metamodel. An important difference between the two approaches is that while MicroART is automatic, MiSAR relies on a manual process for the definition of mapping rules as well as for the code inspection.…”

Section: Related Workmentioning

confidence: 99%

“…For what concerns abstraction, MicroQuality is centered around an architecture model of the system, allowing developers to focus explicitly on architecture-related concerns, instead of imposing the high cognitive burden due to the potentially highly heterogeneous technologies, the internal business logic of the involved microservices, their low-level details, etc. The architecture model of the system can be specified either manually or automatically via pre-existing architecture recovery techniques for MSAs (e.g., [2,14,15]). MicroQuality provides reusable quality attributes via an ecosystem of well-specified and languageindependent software quality attributes for MSAs; the proposed ecosystem fosters reuse by allowing developers to (i) define their own quality attributes, (ii) share them across different systems and organizations, and (iii) reuse quality attributes defined by other developers using the ecosystem.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

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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Towards Micro Service Architecture Recovery: An Empirical Study

Cited by 44 publications

References 13 publications

Microservice transition and its granularity problem: A systematic mapping study

Microservice transition and its granularity problem: A systematic mapping study

On Code Analysis Opportunities and Challenges for Enterprise Systems and Microservices

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

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