基于个人实践分段程序聚类的软件开发工作量估算模糊逻辑系统

C. López-Martín, C. Yáñez-Márquez, A. Gutiérrez-Tornés
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引用次数: 6

摘要

软件度量最常见的应用是开发预测完成软件开发的特定阶段所需的工作量的模型。使用估计模型主要有两个阶段:(1)必须确定模型是否足以描述观测到的(实际)数据,即模型充分性检查;如果结果足够,则(2)在其环境中使用新数据验证估计模型。本文对个人模糊逻辑系统(FLS)与线性回归进行了比较研究。评价标准基于MRE和MER,以及MURE、MMER和pred的方差分析(25)。十八个程序员开发了九十九个程序。从这些程序中生成4个FLS,用于评估由10个开发人员组成的小组开发的60个程序的工作量。结果表明,FLS可以作为评估个人开发工作的替代方法
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fuzzy Logic Systems for Software Development Effort Estimation Based Upon Clustering of Programs Segmented by Personal Practices
The most common application of software metrics is to develop models that predict the effort that will be required to complete certain stages of a software development. There are two main stages for using an estimation model (1) it must be determined whether the model is adequate to describe the observed (actual) data, that is, the model adequacy checking; if it resulted adequate then (2) the estimation model is validated in its environment using new data. In this paper, an investigation aimed to compare personal fuzzy logic systems (FLS) with linear regression is presented. The evaluation criteria is based upon ANOVA of MRE and MER, as well as MURE, MMER and pred(25). Ninety-nine programs were developed by eighteen programmers. From these programs four FLS are generated for estimating the effort of sixty programs developed by a group of ten developers. Results show that a FLS can be used as an alternative for estimating the development effort at personal level
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