Quality requirements are vital to developing successful software products. However, there exist evidence that quality requirements are managed mostly in an “ad hoc” manner and down-prioritized. This may result in insecure, unstable, slow products, and unhappy customers. We have developed a conceptual model for the scoping process of quality requirements – QREME – and an assessment model – Q-REPM – for companies to benchmark when evaluating and improving their quality requirements practices. Our model balances an upfront forward-loop with a data-driven feedback-loop. Furthermore, it addresses both strategic and operational decisions. We have evaluated the model in a multi-case study at two companies in Sweden and three companies in The Netherlands. We assessed the scoping process practices for quality requirements and provided improvement recommendations for which practices to improve. The study confirms the existence of the constructs underlying QREME. The companies perform, in the median, 24% of the suggested actions in Q-REPM. None of the companies work data-driven with their quality requirements, even though four out of five companies could technically do so. Furthermore, on the strategic level, quality requirements practices are not systematically performed by any of the companies. The conceptual model and assessment model capture a relevant view of the quality requirements practices and offer relevant improvement proposals. However, we believe there is a need for coupling quality requirements practices to internal and external success factors to motive companies to change their ways of working. We also see improvement potential in the area of business intelligence for QREME in selecting data sources and relevant stakeholders.

质量要求对于开发成功的软件产品至关重要。但是，有证据表明，质量要求主要以“临时”方式进行管理并降低了优先级。这可能会导致不安全，不稳定，产品运行缓慢以及客户不满意。我们已经为质量需求的范围界定过程开发了一个概念模型– QREME –和评估模型– Q-REPM –供公司在评估和改进其质量要求实践时进行基准测试。我们的模型在前期正向环路与数据驱动的反馈环路之间取得了平衡。此外，它还涉及战略和运营决策。我们在瑞典的两家公司和荷兰的三家公司的多案例研究中评估了该模型。我们针对质量要求评估了范围界定过程的实践，并针对需要改进的实践提供了改进建议。这项研究证实了QREME基础结构的存在。这些公司平均执行了Q-REPM建议行动的24％。尽管五分之四的公司在技术上可以做到这一点，但没有一家公司以数据驱动其质量要求。此外，在战略层面上，任何公司都没有系统地执行质量要求实践。概念模型和评估模型捕获了质量要求实践的相关视图，并提供了相关的改进建议。然而，我们认为，有必要将质量要求实践与内部和外部成功因素相结合，以激励动力公司改变其工作方式。我们还看到QREME在选择数据源和相关利益相关者方面在商业智能领域的改进潜力。