摘要
在网络构件库中构件数量持续增长的情况下,为解决用户无法从质量参差不齐的海量构件中选取优质构件的问题,提出了一种基于构件使用依赖关系的复用可信度计算方法。该方法将构件库作为证据库,首先,对证据库中的构件依赖信息进行采集整理;接着,定义每一个构件的基本信任函数,在此基础上根据构件依赖信息的不同来源为每一条证据设置不同的可信权重值;然后,通过特定的转换算法将由此获得的结果生成构件最终的可信度。实例分析中,利用该方法评估构件取得的结果值与预想中的一致,且与参考构件的内部与外部质量模型所得出的结论相符,但该方法大大降低了构件可信评估的工作量,提高了评估效率。结果表明该方法能够客观反映构件的可信性,可作为构件库中构件检索的一种可信度量机制,帮助实现构件的优质检索和复用。
The number of components is continuously growing in the network component library, it is hard for users to select high-quality components from the massive uneven-quality components. In order to solve the problem, a reuse trust evaluation method based on component use dependency relations was proposed, in which component base was used as an evidence base. Firstly, component dependency relations were collected from evidence base. Secondly, the basic trust function was defined for each component, and the different believable weight value was set up for each evidence according to the different sources of component dependency relations on the above basis. Finally, the final trust value of component was generated by a specific conversion algorithm with the obtained results. In instance analysis, the component evaluation result of the proposed method was consistent with the expectation and the conclusion which was gotten by the internal and external quality model of the reference components. However, the proposed method greatly reduced the workload of component ' s credible evaluation and improved the evaluation efficiency. The results of analysis show that the proposed method can objectively reflect the credibility of components, and can be used as a trusted measurement mechanism of component retrieval in the component library, which helps to realize the high quality retrieval and reuse of components.
出处
《计算机应用》
CSCD
北大核心
2015年第12期3524-3529,共6页
journal of Computer Applications
基金
国家863计划项目(2009AA012201)
国家自然科学基金资助项目(61272107
61202173
61103068)
上海市优秀学科带头人计划项目(10XD1404400)
华为创新研究计划项目(IRP-2013-12-03)
高效能服务器和存储技术国家重点实验室开放基金资助项目(2014HSSA10)
关键词
软件构件
依赖关系
构件描述
可信证据
可信度
software component
dependency relation
component description
credible evidence
trust value