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机构地区:[1]中国科学院软件研究所基础软件国家工程研究中心,北京100190 [2]中国科学院大学,北京100190
出 处:《计算机系统应用》2015年第10期23-31,共9页Computer Systems & Applications
基 金:核心电子器件;高端通用芯片及基础软件产品项目(2012ZX01039-004);国家自然科学基金(61432001;91218302)
摘 要:工作日志是软件外包项目监控项目进展的一个重要手段,它由工作人员填写汇报项目进展.工作日志的质量一定程度上体现了过程执行的质量,但是由于其数量庞大内容琐碎,很难依靠人工完成查看和评估.现有的研究对日志质量的关注较少,因此本文提出一个自动化评估日志质量的方法,该方法利用词法分析、依存句法分析、LDA主题模型对历史日志数据进行分析和挖掘,从结构、内容、主题相关性等方面选取质量特征,通过专家小组标注的方法获得训练数据,使用分类算法建立质量评估模型,通过模型对日志质量进行自动化评估.本文以一个国家核高基项目为案例,实现了一个具有较高准确率的评估模型,结果表明本文的方法能够合理的评估日志质量,为外包单位提供有效的决策支持.Working diary is an important way of monitoring the progress of software outsourcing project. They are committed by project staff as a report of daily work. The quality of working diary can reflect procedure execution of project to some extent, but because the content of working diary is large and trivial, it is hard to check and evaluate rely only on manual work. Existing researches pay little attention to the quality of logs, so we proposed an automated method to evaluate the quality of working diary. Firstly, this method uses the lexical analysis, interdependence syntactic analysis and LDA model to mine and analysis the historical data. Secondly, we extract quality features from aspects such as structure, content, subject relevance, then collect training samples by artificial tagging. Lastly, we establish evaluation model using classification algorithm, through which we get the final evaluation of the work diary. This paper made a case study based on a national project and achieved a highly accurate evaluation model. The result shows that the method can effectively evaluate the quality of working diary, which helps to make decision for outsourcing department.
分 类 号:TP311.5[自动化与计算机技术—计算机软件与理论]
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