摘要
TSP开发过程强调用数据说话,要求较高的精确度,这对于大多数软件企业难以达到,因此应遵循一种“适度度量”的策略。对过程数据的分析不仅可以减少度量的工作量,还可为后续的开发及过程的改进提供参考和建议。该文提出了将形式概念分析(FCA)应用于TSP度量模型中,通过基于概念格的关联规则,挖掘出了有价值的信息。通过实验项目验证了该方法的有效性和实用性。
The development process of TSP emphasizes that data is important and requests for full-scale metrics, but it is difficult for most of software enterprise, so it needs a strategy so-called ＂moderate metrics＂. The analysis of data reduces workload of metrics and provides suggestions and references for the latter developments or process improvement. This paper puts forward the application of formal concept analysis to TSP metrics model, achieves goal of ＂moderate metrics＂ and gains valuable process improvement information by association rules mining based on concept lattice. Some experimental projects prove validity and practicability of application of FCA in TSP measurement model.
出处
《计算机工程》
EI
CAS
CSCD
北大核心
2006年第19期71-73,共3页
Computer Engineering
基金
上海市高等学校科学技术发展基金资助重点项目"软件开发质量管理与控制平台研究"(02AZ86)
关键词
TSP
度量
形式概念分析
内涵缩减
关联规则
Team software process（TSP）
Measurement
Formal concept analysis
Intention reduction
Association rules
