Experimental Study of Quantitative Analysis of Maintenance Effort Using Program Slicing-Based Metrics
Experimental Study of Quantitative Analysis of Maintenance Effort Using Program Slicing-Based Metrics
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DOI：
10.1109/apsec.2012.105
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发表时间：
2012-12
期刊：
影响因子：
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通讯作者：
R. Kula;Kyohei Fushida;Norihiro Yoshida;Hajimu Iida
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文献类型：
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作者：
R. Kula;Kyohei Fushida;Norihiro Yoshida;Hajimu Iida
在软件开发生命周期期间，研究表明，超过75％的项目成本来自维护阶段。由于大多数维护活动围绕源代码，因此对维护阶段中的过程的分析可能会有益。对代码更改所花费的维护工作的准确估算将使资源有效管理。在这项研究中，我们研究了一种定量方法来表达维护工作，并为此提出了一组计划分解的指标。利用时间来解决问题作为维护工作的衡量，我们根据代码的基本基于代码的指标和McCabe的环形复杂性评估了提出的指标。为了消除外部因素，我们对一组预定义的维护活动进行了实验案例研究。结果表明，程序切片指标与维护工作的相关性最强，与维护工作的相关程度适中。相反，代码线与维护工作的相关性较弱。这项研究有助于我们对维护过程分析的持续研究。
During the software development lifecycle, studies have shown that over 75% of project costs originate from the maintenance phase. Analysis of the processes within the maintenance phase could prove beneficial since most maintenance activities revolve around source code. Accurate estimations of the maintenance effort spent on code changes would enable cost effective management of resources. In this research, we investigate a quantitative approach to express maintenance effort, for which a set of program-sliced metrics is proposed. Using the time to resolve an issue as a measure of maintenance effort, we evaluated our proposed metrics against the basic code-based metrics Lines of Code and McCabe's Cyclomatic Complexity. To eliminate outside factors, we performed an experimental case study on a set of pre-defined maintenance activities. Results suggest that program slicing metrics have the strongest correlation with maintenance effort, exhibiting a moderate degree of correlation with maintenance effort. In contrast, Lines of Code has a weak correlation with maintenance effort. This study contributes to our ongoing research into the analysis of maintenance processes.