Several approaches have recently used automated techniques to generate architecture design alternatives by means of optimization techniques. These approaches aim at improving an initial architecture with respect to quality aspects, such as performance, reliability, or maintainability. In this context, each optimization experiment usually produces a different set of architecture alternatives that is characterized by specific settings. As a consequence, the designer is left with the task of comparing such sets to identify the settings that lead to better solution sets for the problem. To assess the quality of solution sets, multi-objective optimization commonly relies on quality indicators. Among these, the quality indicator for the maximum spread estimates the diversity of the generated alternatives, providing a measure of how much of the solution space has been explored. However, the maximum spread indicator is computed only on the objective space and does not consider architectural information (e.g., components structure, design decisions) from the architectural space. In this paper, we propose a quality indicator for the spread that assesses the diversity of alternatives by taking into account architectural features. To compute the spread, we rely on a notion of distance between alternatives according to the way they were generated during the optimization. We demonstrate how our architectural quality indicator can be applied to a dataset from the literature.

翻译：近年来，多种方法通过优化技术自动生成架构设计备选方案。这些方法旨在从性能、可靠性、可维护性等质量维度改进初始架构。在此背景下，每次优化实验通常会生成一组具有特定参数特征的架构备选方案集合。设计人员因此需要比较这些集合，以确定能产生更优问题解集的参数配置。为评估解集质量，多目标优化通常依赖质量指标。其中，最大分布度指标用于评估生成方案的多样性，衡量解空间中被探索范围的大小。然而，该指标仅基于目标空间计算，未考虑架构空间中的架构信息（如组件结构、设计决策）。本文提出一种面向分布性的质量指标，通过纳入架构特征来评估方案的多样性。为计算该指标，我们利用优化过程中方案生成方式的差异定义方案间的距离度量。最后通过文献数据集验证了所提架构质量指标的应用效果。