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Journal articles
ReSIde: Reusable Service Identification from Software Families
Abstract : The clone-and-own approach becomes a common practice to quickly develop Software Product Variants (SPVs) that meet variability in user requirements. However, managing the reuse and maintenance of the cloned codes is a very hard task. Therefore, we aim to analyze SPVs to identify cloned codes and package them using a modern systematic reuse approach like Service-Oriented Architecture (SOA). The objective is to benefit from all the advantages of SOA when creating new SPVs. The development based on services in SOA supports the software reuse and maintenance better than the development based on individual classes in monolithic object-oriented software. Existing service identification approaches identify services based on the analysis of a single software product. These approaches are not able to analyze multiple SPVs to identify reusable services of cloned codes. Identifying services by analyzing several SPVs allows to increase the reusability of identified services. In this paper, we propose ReSIde (Reusable Service Identification): an automated approach that identifies reusable services from a set of object-oriented SPVs. This is based on analyzing the commonality and the variability between SPVs to identify the implementation of reusable functionalities corresponding to cloned codes that can be packaged as reusable services. To validate ReSIde, we have applied it on three product families of di↵erent sizes. The results show that the services identified based on the analysis of multiple product variants using ReSIde are more reusable than services identified based on the analysis of singular ones.
Cited literature [108 references]
https://hal.sorbonne-universite.fr/hal-02910330
Contributor : Tewfik Ziadi <>
Submitted on : Saturday, August 1, 2020 - 10:52:26 PM
Last modification on : Monday, May 17, 2021 - 4:56:02 PM
Long-term archiving on: : Monday, November 30, 2020 - 12:45:33 PM
Contributor : Tewfik Ziadi <>
Submitted on : Saturday, August 1, 2020 - 10:52:26 PM
Last modification on : Monday, May 17, 2021 - 4:56:02 PM
Long-term archiving on: : Monday, November 30, 2020 - 12:45:33 PM
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