A Genetic Algorithm to Find the Adequate Granularity for Service Interfaces

被引：3

作者：

Romano, Daniele ^{[1
]}

Pinzger, Martin ^{[2
]}

机构：

[1] Delft Univ Technol, Software Engn Res Grp, Delft, Netherlands

[2] Univ Klagenfurt, Software Engn Res Grp, Klagenfurt, Austria

来源：

2014 IEEE WORLD CONGRESS ON SERVICES (SERVICES) | 2014年

关键词：

SOA; services; granularity; genetic algorithms;

D O I：

10.1109/SERVICES.2014.91

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The relevance of the service interfaces' granularity and its architectural impact have been widely investigated in literature. Existing studies show that the granularity of a service interface, in terms of exposed operations, should reflect their clients' usage. This idea has been formalized in the Consumer-Driven Contracts pattern (CDC). However, to the best of our knowledge, no studies propose techniques to assist providers in finding the right granularity and in easing the adoption of the CDC pattern. In this paper, we propose a genetic algorithm that mines the clients' usage of service operations and suggests Fac, ade services whose granularity reflect the usage of each different type of clients. These services can be deployed on top of the original service and they become contracts for the different types of clients satisfying the CDC pattern. A first study shows that the genetic algorithm is capable of finding Fac, ade services and outperforms a random search approach.

引用

页码：478 / 485

页数：8

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