How flexible must a transformation approach for variability models and custom variability representations be?

Kevin Feichtinger, Rick Rabiser
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引用次数: 2

Abstract

A plethora of variability modeling approaches has been developed in the last 30 years. Feature modeling approaches are probably the most common and well-known approaches. All existing variability modeling approaches have their benefits and drawbacks and have been shown to be useful at least in certain use cases. Nevertheless, industry frequently develops their own custom solutions to manage variability because they struggle picking an approach from the (still growing) number of modeling approaches available. Therefore, we work towards a transformation approach, which enables researchers and practitioners alike to compare different (custom) variability modeling approaches and representations and switch in between them at least (semi-)automatically. In this paper, we discuss ongoing challenges for the transformation approach regarding the implementation of the transformations and the expected flexibility of the approach. We present our research agenda towards a flexible and adaptable transformation approach for well-known variability modeling approaches and custom variability representations used in industry.
可变性模型和自定义可变性表示的转换方法必须有多灵活?
在过去的30年里,出现了大量的变率建模方法。特征建模方法可能是最常见和最知名的方法。所有现有的可变性建模方法都有其优点和缺点,并且至少在某些用例中已被证明是有用的。然而,业界经常开发他们自己的定制解决方案来管理可变性,因为他们很难从可用的(仍在增长的)建模方法中选择一种方法。因此,我们致力于一种转换方法,它使研究人员和实践者能够比较不同的(定制的)可变性建模方法和表示,并至少(半)自动地在它们之间切换。在本文中,我们讨论了关于转换的实现和该方法的预期灵活性的转换方法正在面临的挑战。我们提出了针对众所周知的可变性建模方法和工业中使用的自定义可变性表示的灵活和适应性转换方法的研究议程。
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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