Exploiting the enumeration of all feature model configurations: a new perspective with distributed computing

J. Galindo, M. Acher, Juan M. Tirado, Cristian Vidal, B. Baudry, David Benavides
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引用次数: 15

Abstract

Feature models are widely used to encode the configurations of a software product line in terms of mandatory, optional and exclusive features as well as propositional constraints over the features. Numerous computationally expensive procedures have been developed to model check, test, configure, debug, or compute relevant information of feature models. In this paper we explore the possible improvement of relying on the enumeration of all configurations when performing automated analysis operations. We tackle the challenge of how to scale the existing enumeration techniques by relying on distributed computing. We show that the use of distributed computing techniques might offer practical solutions to previously unsolvable problems and opens new perspectives for the automated analysis of software product lines.
利用所有特征模型配置的枚举:分布式计算的新视角
特征模型被广泛用于根据强制性、可选性和排他性特征以及特征上的命题约束对软件产品线的配置进行编码。为了模型检查、测试、配置、调试或计算特征模型的相关信息,已经开发了许多计算开销很大的过程。在本文中,我们探讨了在执行自动化分析操作时依赖于所有配置枚举的可能改进。我们解决了如何通过依赖分布式计算来扩展现有枚举技术的挑战。我们展示了分布式计算技术的使用可能为以前无法解决的问题提供实用的解决方案,并为软件产品线的自动化分析开辟了新的视角。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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