DocumentCode
176187
Title
Enhancing Clone-and-Own with Systematic Reuse for Developing Software Variants
Author
Fischer, Shannon ; Linsbauer, Lukas ; Lopez-Herrejon, Roberto Erick ; Egyed, Alexander
Author_Institution
Johannes Kepler Univ., Linz, Austria
fYear
2014
fDate
Sept. 29 2014-Oct. 3 2014
Firstpage
391
Lastpage
400
Abstract
To keep pace with the increasing demand for custom-tailored software systems, companies often apply a practice called clone-and-own, whereby a new variant of a software system is built by coping and adapting existing variants. Instead of a single and configurable system, clone-and-own leads to ad hoc product portfolios of multiple yet similar variants that soon become impossible to maintain effectively. Clone-and-own has widespread industrial use because it requires no major upfront investments and is intuitive, but it lacks a methodology for systematic reuse. In this work we propose ECCO (Extraction and Composition for Clone-and-Own), a novel approach to enhance clone and-own that actively supports the development and maintenance of software product variants. A software engineer selects the desired features and ECCO finds the proper software artifacts to reuse and then provides guidance during the manual completion by hinting which software artifacts may need adaptation. We evaluated our approach on 6 case studies, covering 402 variants having up to 344KLOC, and found that precision and recall of composed products quickly reach a near optimum (>95% reuse).
Keywords
investment; software maintenance; software reusability; ECCO approach; ad hoc product portfolios; clone-and-own enhancement; custom-tailored software systems; extraction and composition for clone-and-own approach; software artifacts; software product variant maintenance; software variant development; systematic reuse; Color; Feature extraction; Java; Manuals; Portfolios; Software; Solids; clone-and-own; feature interactions; features; product variants; reuse;
fLanguage
English
Publisher
ieee
Conference_Titel
Software Maintenance and Evolution (ICSME), 2014 IEEE International Conference on
Conference_Location
Victoria, BC
ISSN
1063-6773
Type
conf
DOI
10.1109/ICSME.2014.61
Filename
6976105
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