摘要： 软件开发的复杂性决定了理想的软件复杂性度量模型既应具有包容众多复杂因素的能力，又要有构造灵活的功能。迄今为止，人们提出的众多模型，由于设定了很多近乎苛刻的条件，使它们难以具有普适性。Bayes网提供了解决这一问题的有力工具。该文建立起一种基于Bayes网的软件残留错误数度量模型，并对此进行了分析。

关键词: Bayes网, 软件复杂度, 软件残留错误数

Abstract: Owing to the complexity of software development, the software complexity estimation model should not only have the capability of dealing with multiple complex factors, but also provide the function of flexibility in construction. So far, no such models are universally applicable. The main reason for this is of too many conditions, thus making these models introvert. Bayesian network is a powerful tool for solving this problem, which exhibits strong adaptability in dealing with problems involving complex variant factors. In the paper, an estimation model of the number of remaining software errors based on Bayesian network is established and analyzed.

中图分类号: 

• TP311.1