基于熵的AO程序复杂性度量(英文)  

Entropy-based Complexity Measure for Aspect-Oriented Program

作　　者：郭铭铭[1] 窦建华[1] 杨彬[2] 曹璟[2] 

机构地区：[1]计算机与信息学院合肥工业大学,合肥230009 [2]计算机科学与工程学院东南大学,南京210096

出　　处：《南京大学学报（自然科学版）》2007年第5期509-519,共11页Journal of Nanjing University（Natural Science）

摘　　要：AOP(aspect-oriented programming)是一种新的程序设计范式,它能够有效解决横切关注点分离问题.由于AO系统的行为依赖于aspect与类之间的交互,因而定义一种新的、适合于AO的复杂性度量,以更加有效的理解和维护AO程序就很有必要.提出了一种新的复杂性度量,用以评估AO系统中aspect的复杂性.首先定义了aspect的信息流图,用以描述组成aspect的元素之间的交互和aspect与其他程序单元的交互;在此基础上,提出了一种基于信息熵的aspect复杂性度量,它从aspect负载的平均信息量角度量化aspect的复杂性.分析了它的外部行为特性,并使用多个AO项目进行了验证.实验结果表明,该度量反映了aspect的设计度量,能够有效的预测aspect的复杂性.Aspect-oriented programming has been proposed as a new paradigm for improving separation of crosscutting concerns. The behavior of an aspect-oriented system depends on the interaction between aspects and classes. The metrics that adapt to this new paradigm are very favorable for effective understanding and maintaining the aspect-oriented software. This paper presents an entropy-based complexity measure to assess aspects in aspect-oriented programs. The aspect information flow graph is developed to represent the inter-aspect and intra-aspect interaction associated with an aspect. Based on this graph, the complexity measure is defined in terms of the average amount of information conveyed by an aspect. The behavior properties of the measure are discussed and validated by several aspect-oriented projects. The experimental results show that the measure has a positive correlation with the aspect design measures and can be used to predict the complexity of aspects.

关 键 词：复杂性度量 AOP 信息熵 

分 类 号：TP311.1[自动化与计算机技术—计算机软件与理论]