2022
DOI: 10.1016/j.infsof.2022.106996
|View full text |Cite
|
Sign up to set email alerts
|

Improving microservices extraction using evolutionary search

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1

Citation Types

0
3
0

Year Published

2022
2022
2024
2024

Publication Types

Select...
4
3

Relationship

0
7

Authors

Journals

citations
Cited by 14 publications
(3 citation statements)
references
References 39 publications
0
3
0
Order By: Relevance
“…Sellami et al [31] present MSExtractor, an approach to decompose monoliths written in an object-oriented (OO) programming language in microservices. The application is conceived as a set of classes that are automatically classified as either inner, if they are only used as internal components, or interfaces, if they expose public endpoints to the users.…”
Section: Related Workmentioning
confidence: 99%
“…Sellami et al [31] present MSExtractor, an approach to decompose monoliths written in an object-oriented (OO) programming language in microservices. The application is conceived as a set of classes that are automatically classified as either inner, if they are only used as internal components, or interfaces, if they expose public endpoints to the users.…”
Section: Related Workmentioning
confidence: 99%
“…In this paper, we distinguish these two types of elements mainly for better capturing the associations across microservices. In particular, we employ the concept of interface classes and inner classes (Sellami et al, 2022) to distinguish between the two aforementioned classes, respectively. In the meantime, we use the concept of entity to embody both of these classes within a microservice.…”
Section: Basic Definitionsmentioning
confidence: 99%
“…Nevertheless, few coupling measurement in the SE literature has been proposed for describing the degree to which the microservices in a software system are related. Instead, some coupling metrics that were proposed for object-oriented or serviceoriented paradigms have been adapted and applied now in MSA, such as Sellami et al (2022), Carvalho et al (2020), Mazlami et al (2017) and Li et al (2019). Most of these metrics are generally based on simple counts of coupling ''evidence'' in a system, such as the number of dependencies (e.g., static calls) between microservices and the number of software elements (e.g., classes) involved in the dependencies.…”
Section: Introductionmentioning
confidence: 99%