Which Process Metrics Are Significantly Important to Change of Defects in Evolving Projects: An Empirical Study

被引:6
作者
Jiang, Li [1 ,2 ]
Jiang, Shujuan [1 ,2 ]
Gong, Lina [1 ,2 ,3 ]
Dong, Yue [4 ]
Yu, Qiao [5 ]
机构
[1] China Univ Min & Technol, Sch Comp Sci & Technol, Xuzhou 221116, Jiangsu, Peoples R China
[2] Minist Educ, Mine Digitizat Engn Res Ctr, Xuzhou 221116, Jiangsu, Peoples R China
[3] Zaozhuang Univ, Dept Informat Sci & Engn, Zaozhuang 277160, Peoples R China
[4] China Univ Min & Technol, Sun Yueqi Honors Coll, Xuzhou 221116, Jiangsu, Peoples R China
[5] Jiangsu Normal Univ, Sch Comp Sci & Technol, Xuzhou 221116, Jiangsu, Peoples R China
基金
中国国家自然科学基金;
关键词
Software; Correlation; Complexity theory; Software metrics; Education; Computer science; Process metrics; software defect prediction; software evolution; CODE CHURN; FAULT-PRONENESS; SOFTWARE; PREDICTION; MODELS; COMPLEXITY; NUMBER;
D O I
10.1109/ACCESS.2020.2994528
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Process metrics can reflect the software development process and the code changes which are the main causes of defects. So, recently, the researches have put more emphasis on process metrics in the field of software defect prediction. For evolving projects, it is more meaningful to study whether the software module introduces or eliminates defects or not, not whether the software module is defective or defect-free. However, no such work is available in the literature focusing on the change of defect state. Discovering the factors that influence the change of defect state in the process of software development can help us to understand the causes of software defects and improve the quality of subsequent software versions. Therefore, this paper presents an extensive empirical study on which process metrics are significantly important to change of defects in evolving projects. Five process metrics of 37 versions in 12 software projects are collected. We not only analyze the class correlation values and the classification performance values among five process metrics, but also perform statistical analysis to verify whether the experimental results are of practical value. The experimental results indicate that Number of Distinct Committers plays a significantly important role in the change of defect state, especially for elimination of defects, and Number of Revisions is the second, whereas Degree of Code Modification is the last. In addition, Average Number of Modified Lines is superior to Number of Modified Lines. Based on the experimental results, some suggestions for software development and software defect prediction are also discussed.
引用
收藏
页码:93705 / 93722
页数:18
相关论文
共 53 条
[1]  
AHA DW, 1991, MACH LEARN, V6, P37, DOI 10.1007/BF00153759
[2]  
[Anonymous], 2010, P 18 ACM SIGSOFT INT, DOI DOI 10.1145/1882291.1882311
[3]  
[Anonymous], SOFTWARE PRODUCT MET
[4]  
[Anonymous], 2006, P 5 INT S EMP SOFTW, DOI [10.1145/1159733.1159739, DOI 10.1145/1159733.1159739.]
[5]  
[Anonymous], 2007, Third International Workshop on Predictor Models in Software Engineering (PROMISE'07: ICSE Workshops 2007)
[6]   Approximations of functions by a multilayer perceptron: a new approach [J].
Attali, JG ;
Pages, G .
NEURAL NETWORKS, 1997, 10 (06) :1069-1081
[7]   SMOTE: Synthetic minority over-sampling technique [J].
Chawla, Nitesh V. ;
Bowyer, Kevin W. ;
Hall, Lawrence O. ;
Kegelmeyer, W. Philip .
2002, American Association for Artificial Intelligence (16)
[8]   A METRICS SUITE FOR OBJECT-ORIENTED DESIGN [J].
CHIDAMBER, SR ;
KEMERER, CF .
IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, 1994, 20 (06) :476-493
[9]   Empirical analysis of change metrics for software fault prediction [J].
Choudhary, Garvit Rajesh ;
Kumar, Sandeep ;
Kumar, Kuldeep ;
Mishra, Alok ;
Catal, Cagatay .
COMPUTERS & ELECTRICAL ENGINEERING, 2018, 67 :15-24
[10]  
Cohen J., 1988, STAT POWER ANAL BEHA, DOI 10.4324/9780203771587