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2018 | OriginalPaper | Buchkapitel

A Behavior-Based Framework for Assessing Product Line-Ability

verfasst von : Iris Reinhartz-Berger, Anna Zamansky

Erschienen in: Advanced Information Systems Engineering

Verlag: Springer International Publishing

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Abstract

Systems are typically not developed from scratch, so different kinds of similarities between them exist, challenging their maintenance and future development. Software Product Line Engineering (SPLE) proposes methods and techniques for developing reusable artifacts that can be systematically reused in similar systems. Despite the potential benefits of SPLE to decrease time-to-market and increase product quality, it requires a high up-front investment and hence SPLE techniques are commonly adopted in a bottom-up approach, after individual systems have already been developed. Deciding whether to turn existing systems into a product line – referred to as product line-ability – involves many aspects and requires some tooling for analyzing similarities and differences among systems. In this paper we propose a framework for the identification of “similarly behaving” artifacts and analyzing their potential reuse in the context of product lines. This framework provides metrics for calculating behavior similarity and a method for analyzing the product line-ability of a set of products. The framework has been integrated into a tool named VarMeR – Variability Mechanisms Recommender, whose aim is to systematically guide reuse.

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Fußnoten
1
Note that the behavior representation considers the impact of procedure calls, such as doMergeSort and mergeParts for MergeSort. Nevertheless, the approach represents only public operations, assuming that private and protected operations may be defined for implementation purposes. Our assumption is that differences in such operations do not necessarily imply differences in intentional behavior.
 
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Metadaten
Titel
A Behavior-Based Framework for Assessing Product Line-Ability
verfasst von
Iris Reinhartz-Berger
Anna Zamansky
Copyright-Jahr
2018
DOI
https://doi.org/10.1007/978-3-319-91563-0_35