Qualitative simulation model for software engineering process

He Zhang, Mingkui Huo, B. Kitchenham, D. R. Jeffery
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引用次数: 33

Abstract

Software process simulation models hold out the promise of improving project planning and control. However, quantitative models require a very detailed understanding of the software process. In particular, process knowledge needs to be represented quantitatively which requires extensive, reliable software project data. When such data is lacking, quantitative models must impose severe constraints, restricting the value of the models. In contrast qualitative models are able to cope with imprecise knowledge by reasoning at a more abstract level. This paper illustrates the value and flexibility of qualitative models by developing a model of the software staffing process and comparing it with other quantitative staffing models. We show that the qualitative model provides more insights into the staffing process than the quantitative models because it requires fewer constraints and can thus simulate more behaviors. In particular, the qualitative model produces three possible outcomes: adding staff can increases project duration (i.e. Brooks' Law), adding staff may not affect duration, or adding staff may decrease duration. The qualitative model allows us to determine the conditions under which the different outcomes can occur
软件工程过程的定性仿真模型
软件过程仿真模型有望改善项目计划和控制。然而,定量模型需要对软件过程有非常详细的了解。特别是,过程知识需要定量地表示,这需要广泛的、可靠的软件项目数据。当缺乏此类数据时,定量模型必须施加严格的约束,从而限制了模型的价值。相比之下,定性模型能够通过在更抽象的层次上推理来处理不精确的知识。本文通过开发软件人员配置过程模型,并与其他定量人员配置模型进行比较,说明了定性模型的价值和灵活性。我们表明,定性模型比定量模型提供了更多关于人员配置过程的见解,因为它需要更少的约束,因此可以模拟更多的行为。特别是,定性模型产生了三种可能的结果:增加人员可以增加项目持续时间(即布鲁克斯定律),增加人员可能不影响持续时间,或者增加人员可能减少持续时间。定性模型使我们能够确定不同结果可能发生的条件
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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