Catalog and detection techniques of microservice anti-patterns and bad smells : a tertiary study |
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Author: | Cerny, Tomas1; Abdelfattah, Amr S.2; Maruf, Abdullah Al2; |
Organizations: |
1SIE, University of Arizona, Tucson, AZ, USA 2Baylor University, Waco, TX, USA 3FHV Vorarlberg University of Applied Sciences, Dornbirn, Austria
4Tampere University, Tampere, Finland
5University of Oulu, Oulu, Finland |
Format: | article |
Version: | published version |
Access: | open |
Online Access: | PDF Full Text (PDF, 1.1 MB) |
Persistent link: | http://urn.fi/urn:nbn:fi-fe20231024141154 |
Language: | English |
Published: |
Elsevier,
2023
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Publish Date: | 2023-10-24 |
Description: |
AbstractBackground: Various works investigated microservice anti-patterns and bad smells in the past few years. We identified seven secondary publications that summarize these, but they have little overlap in purpose and often use different terms to describe the identified anti-patterns and smells. Objective: This work catalogs recurring bad design practices known as anti-patterns and bad smells for microservice architectures, and provides a classification into categories as well as methods for detecting these practices. Method: We conducted a systematic literature review in the form of a tertiary study targeting secondary studies identifying poor design practices for microservices. Results: We provide a comprehensive catalog of 58 disjoint anti-patterns, grouped into five categories, which we derived from 203 originally identified anti-patterns for microservices. Conclusion: The results provide a reference to microservice developers to design better-quality systems and researchers who aim to detect system quality based on anti-patterns. It also serves as an anti-pattern catalog for development-aiding tools, which are not currently available for microservice system development but could mitigate quality degradation throughout system evolution. see all
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Series: |
Journal of systems and software |
ISSN: | 0164-1212 |
ISSN-E: | 1873-1228 |
ISSN-L: | 0164-1212 |
Volume: | 206 |
Article number: | 111829 |
DOI: | 10.1016/j.jss.2023.111829 |
OADOI: | https://oadoi.org/10.1016/j.jss.2023.111829 |
Type of Publication: |
A1 Journal article – refereed |
Field of Science: |
113 Computer and information sciences |
Subjects: | |
Funding: |
This material is based upon work supported by the National Science Foundation, United States under Grant No. 1854049 and Grant No. 2245287, a grant from Red Hat Research https://research.redhat.com, a grant from the Ulla Tuominen Foundation (Finland), and a grant from the Academy of Finland (grant n. 349488 - MuFAno). |
Academy of Finland Grant Number: |
349488 |
Detailed Information: |
349488 (Academy of Finland Funding decision) |
Copyright information: |
© 2023 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
https://creativecommons.org/licenses/by/4.0/ |