通过自动化相似性匹配增强需求重用

M. Mannion, H. Kaindl
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引用次数: 0

摘要

一些社会经济趋势正在推动客户对个性化的需求。许多供应商通过提供供应商主导的软件产品设计定制选择(“大规模定制”)来应对。有些还提供以客户为导向的软件产品设计选择(“大规模个性化”)。本教程将介绍这些概念,并探讨其对软件产品线开发的影响。一个特殊的技术挑战是能够大规模地响应和管理越来越多的常见的、由供应商主导和由客户主导的特性。我们将讨论应对这一挑战的两种不同方法。一种基于特征建模,另一种基于案例推理,后者依赖于测量相似性。然后,我们将描述一个特定的产品相似性评估过程,其中从产品线特征模型配置的产品被表示为加权二进制字符串,使用二进制字符串度量比较产品之间的总体相似性,并且可以通过修改权重来探索单个特征组合对产品相似性的重要性。我们将用手机工作的例子来说明我们的想法,并讨论这种方法的一些优点和局限性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enhancing requirements reuse through automated similarity matching
Several socio-economic trends are driving customer demands towards individualization. Many suppliers are responding by offering supplier-led software product design customization choices ("mass customization"). Some are also offering customer-led software product design choices ("mass personalization"). This tutorial introduces these concepts and explores the implications for software product line development. One particular technical challenge is being able to respond to and manage at scale the increasing variety of common, supplier-led and customer-led features. We will discuss two different approaches to address this challenge. One is grounded in feature modelling, the other in case-based reasoning, where the latter relies on measuring similarities. We will then describe a specific product similarity evaluation process in which a product configured from a product line feature model is represented as a weighted binary string, the overall similarity between products is compared using a binary string metric, and the significance of individual feature combinations for product similarity can be explored by modifying the weights. We will illustrate our ideas with mobile phone worked examples, and discuss some of the benefits and limitations of this approach.
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