Towards microservice smells detection

Pigazzini, Ilaria; Fontana, Francesca Arcelli; Lenarduzzi, Valentina; Taibi, Davide

doi:10.1145/3387906.3388625

Cited by 55 publications

(35 citation statements)

References 7 publications

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“…Pigazzini et al 48 propose a first solution for automatically identifying three smells (viz., cyclic dependencies, hardcoded endpoints, and shared persistence) in microservice‐based applications. Their solution builds on top of an existing tool for detecting architectural smells in software projects, 49 which the authors adapted to work with microservice‐based architectures.…”

Section: Related Workmentioning

confidence: 99%

“…10 At the same time, to the best of our knowledge, ours is the first solution enabling to both identify andresolve the smells affecting the architecture of a microservice-based application, with such architecture being represented with an open standard, that is, the OASIS standard TOSCA. 11 Pigazzini et al 48 propose a first solution for automatically identifying three smells (viz., cyclic dependencies, hardcoded endpoints, and shared persistence) in microservice-based applications. Their solution builds on top of an existing tool for detecting architectural smells in software projects, 49 which the authors adapted to work with microservice-based architectures.…”

Section: 3mentioning

confidence: 99%

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The μTOSCA toolchain: Mining, analyzing, and refactoring microservice‐based architectures

et al. 2021

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Summary Exploiting microservices to architect enterprise applications is becoming commonplace. This makes it crucial to provide some support for designing and analyzing microservice‐based applications, for example, for understanding whether a microservice‐based application adheres to the main design principles of microservices and for choosing how to refactor it when this is not the case. To provide such support, in this article we present the μTOSCA toolchain. More precisely, we first introduce the μTOSCA model to represent the architecture of microservice‐based applications with the OASIS standard TOSCA. We then describe a technique to automatically mine the architecture of a microservice‐based application and represent it with μTOSCA, given the Kubernetes deployment of the application. We also present a methodology to analyze the μTOSCA representation of a microservice‐based architecture to systematically identify the architectural smells potentially affecting the corresponding application and to resolve them. Finally, we present two prototype tools, μMiner and μFreshener, implementing our mining solution and the support for identifying and resolving architectural smells in microservice‐based applications, respectively. We then assess —by discussing some case studies— how effectively μMiner, μFreshener, and the μTOSCA toolchain can support researchers and practitioners working with microservices.

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Section: Related Workmentioning

confidence: 99%

Section: 3mentioning

confidence: 99%

The μTOSCA toolchain: Mining, analyzing, and refactoring microservice‐based architectures

et al. 2021

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“…In this situation, their use of static-code analysis also allowed them to identify concrete refactoring solutions that would counter these antipatterns. A paper by Pigazzini et al [29] also uses static-code analysis for improving microservice architecture by implementing detection methods for three different microservice smells in a pre-existing tool called Arcan. Baresi et al [15] iteratively map OpenAPI specifications to concepts in reference vocabulary, which are computed to be the best matches.…”

Section: Static Analysismentioning

confidence: 99%

Section: Pattern-based Analysismentioning

confidence: 99%

“…Many of the articles we processed considered identifying development patterns [27,[29][30][31]61,62]. Pattern-based analysis mostly employs static analysis to recognize specific patterns in the source code [27,29,31]. Moreover, architectural patterns and mathematical model checking approaches have also been explored in related studies [30,61,62].…”

Section: Pattern-based Analysismentioning

confidence: 99%

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On Microservice Analysis and Architecture Evolution: A Systematic Mapping Study

et al. 2021

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Microservice architecture has become the leading design for cloud-native systems. The highly decentralized approach to software development consists of relatively independent services, which provides benefits such as faster deployment cycles, better scalability, and good separation of concerns among services. With this new architecture, one can naturally expect a broad range of advancements and simplifications over legacy systems. However, microservice system design remains challenging, as it is still difficult for engineers to understand the system module boundaries. Thus, understanding and explaining the microservice systems might not be as easy as initially thought. This study aims to classify recently published approaches and techniques to analyze microservice systems. It also looks at the evolutionary perspective of such systems and their analysis. Furthermore, the identified approaches target various challenges and goals, which this study analyzed. Thus, it provides the reader with a roadmap to the discipline, tools, techniques, and open challenges for future work. It provides a guide towards choices when aiming for analyzing cloud-native systems. The results indicate five analytical approaches commonly used in the literature, possibly in combination, towards problems classified into seven categories.

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Impacts, causes, and solutions of architectural smells in microservices: An industrial investigation

et al. 2022

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As a recently predominant architecture style, MicroService Architecture (MSA) is likely to suffer the issues of poor maintainability due to inappropriate microservice boundaries. Architectural Smell (AS), as a metaphor for potential architectural issues that may have negative impacts on software maintenance, can be used to pinpoint refactoring opportunity for evolving microservice boundary. However, existing studies mostly focus on AS detection with little further investigation on the possible impacts, causes, and solutions of AS, which does little help in addressing the bad smells in architecture. Our goal in this study is to bridge this gap by investigating the possible impacts, causes, and solutions of AS in MSA-based systems. An industrial case study is carried out to collect repository data and practitioners' views on six typical ASes in a real MSA-based telecommunication system. Statistical Analysis and Coding techniques are used in the analyses of quantitative and qualitative data respectively.The results show that AS influences the modularity, modifiability, analyzability, and testability of the MSA-based system, which further induce extra cross-team communication, change-and fault-prone microservices. To explore the causes for AS, a five-aspect conceptual classification with technology, project, organization, business, and professional is proposed, in which the business and organization aspects take the major roles. Both technical and non-technical solutions are distilled to deal with ASes despite potential constraints. These results and their comparison to current literature are discussed, which provide practical implications in coping with AS in microservices.

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Towards microservice smells detection

Cited by 55 publications

References 7 publications

The μTOSCA toolchain: Mining, analyzing, and refactoring microservice‐based architectures

The μTOSCA toolchain: Mining, analyzing, and refactoring microservice‐based architectures

On Microservice Analysis and Architecture Evolution: A Systematic Mapping Study

Impacts, causes, and solutions of architectural smells in microservices: An industrial investigation

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