论文标题
一种基于模糊的优化方法，用于将价值依赖性集成到软件需求选择中
A Fuzzy-Based Optimization Method for Integrating Value Dependencies into Software Requirement Selection
论文作者
论文摘要
软件需求选择旨在在尊重预算的同时找到具有最高价值的最佳需求子集。但是，需求的价值可能取决于最佳子集中的其他要求。但是，现有的需求选择方法不考虑价值依赖性，从而增加了价值损失的风险。为了解决这个问题，我们提出了依赖性意识要求选择（DARS）方法，其中有两个主要组成部分：（i）一种基于模糊的技术，用于识别和建模价值依赖性，以及（ii）一个整数编程模型，该模型在软件需求选择中考虑了价值依赖性。对于量化价值依赖性很难的情况，我们提出了一个替代优化模型。通过详尽的模拟证明了DARS的可伸缩性及其在降低价值损失风险方面的有效性。
Software requirement selection aims to find an optimal subset of the requirements with the highest value while respecting the budget. But the value of a requirement may depend on the presence or absence of other requirements in the optimal subset. Existing requirement selection methods, however, do not consider Value Dependencies, thus increasing the risk of value loss. To address this, we have proposed Dependency-Aware Requirement Selection (DARS) method with two main components: (i) a fuzzy-based technique for identifying and modeling value dependencies, and (ii) an Integer Programming model that takes into account value dependencies in software requirement selection. We have further, proposed an alternative optimization model for situations where quantifying value dependencies is hard. The scalability of DARS and its effectiveness in reducing the risk of value loss are demonstrated through exhaustive simulations.
