Selecting the appropriate requirements to develop in the next release of an open market software product under evolution, is a compulsory step of each software development project. This selection should be done by maximizing stakeholders' satisfaction and minimizing development costs, while keeping constraints. In this work we investigate what is the requirements interactions impact when searching for solutions of the bi-objective Next Release Problem. In one hand, these interactions are explicitly included in two algorithms: a branch and bound algorithm and an estimation of distribution algorithm (EDA). And on the other, we study the performance of these not previously used solving approaches by applying them in several instances of small, medium and large size data sets. We find that interactions inclusion do enhance the search and when time restrictions exists, as in the case of the bi-objective Next Release Problem, EDAs have proven to be stable and reliable locating a large number of solutions on the reference Pareto front.
翻译:选择在即将推出的开放市场软件产品中开发的适当要求,是每个软件开发项目的一个强制步骤。这一选择应当通过最大限度地提高利益攸关方的满意度和最大限度地降低开发成本,同时保持限制。在这项工作中,我们在寻找双目标下一个发布问题解决方案时调查需求互动影响是什么。一方面,这些互动明确包含在两种算法中:分支和约束算法,以及分配算法的估计。另一方面,我们研究这些以前没有使用过的解决方法的绩效,在小型、中型和大型数据集中应用这些方法。我们发现,互动包容确实加强了搜索,而且在存在时间限制时,如双目标下一个发布问题,EDA已证明稳定和可靠地在参考的Pareto前方找到大量解决方案。