Supporting product configuration in application engineering using EXConfig
Authors: 
Bo Zhang, 
Martin BeckerAuthors Info & Claims
Pages 324 - 327
Abstract
Nowadays systems are often developed following the product line approach in order to reduce time to market, achieve lower cost, and ensure high quality. To this end, common and variable requirements of product variants are specified as features in a feature model, so that each product variant can be configured and customized along the development lifecycle. While developers in family engineering tend to use variability management tools (e.g., pure::variants) for feature modeling and developing core assets for reuse, such sophisticated tools might be too complicated and inappropriate for product configuration in application engineering. In order to solve this challenge, this paper introduces an Excel-based product configurator called EXConfig, which focuses on product line features in the problem space and supports staged product configuration in application engineering. This tool can be easily customized and integrated with other system design tools or variability management tools, which connects application engineering and family engineering in development. The usage of this tool and its integration have been validated several times in industry.
References
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Index Terms
- Supporting product configuration in application engineering using EXConfig
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Sponsors
- Huawei Technologies Co. Ltd.: Huawei Technologies Co. Ltd.
- Key Laboratory of High Confidence Software Technologies: Key Laboratory of High Confidence Software Technologies, Ministry of Education
- DC Holdings: Digital China Holdings Limited
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 16 September 2016
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- Research-article
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SPLC '16
Sponsor:
- Huawei Technologies Co. Ltd.
- Key Laboratory of High Confidence Software Technologies
- DC Holdings
SPLC '16: The 20th International Systems and Software Product Line Conference
September 16 - 23, 2016
Beijing, China
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Overall Acceptance Rate 167 of 463 submissions, 36%
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