A Method for Measuring Similarity of Software Defect Data

被引：0
|
作者：
Wan, Lin [1 ]
Yang, Tengxiang [1 ]
Liu, Haining [2 ]
机构：
[1] Acad Armored Force Engn, Dept Informat Engn, Beijing, Peoples R China
[2] China Acad Ordnance Sci, Beijing, Peoples R China
来源：
2017 IEEE 2ND ADVANCED INFORMATION TECHNOLOGY, ELECTRONIC AND AUTOMATION CONTROL CONFERENCE (IAEAC) | 2017年
关键词：
fuzzy cluster; similarity; software defects;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The essence of the classification method is the similarity measure, which divides the objects with the same attributes into one class for analysis. In this paper, we first study the similarity measure method of mixed attributes of data mining, and introduce the attribute weight calculation method of defect data to take into account the influence of different attributes on the similarity measurement. It not only reflects the degree of similarity between the attributes of the defect data, but also reflects the distance between the attributes. In this paper, the defect data are analyzed and the results are measured. The experimental results show that the improved similarity measure has a certain degree of improvement in accuracy.
引用
收藏
页码：1108 / 1112
页数：5
相关论文
共 50 条
  • [41] A Case Study of Measuring Degeneration of Software Architectures From A Defect Perspective
    Li, Zude
    Long, Jun
    2011 18TH ASIA-PACIFIC SOFTWARE ENGINEERING CONFERENCE (APSEC 2011), 2011, : 242 - 249
  • [42] Software PLL as a Method for Measuring the Mains Frequency
    Serov, Andrey N.
    Shatokhin, Aleksander A.
    Serov, Nikolay A.
    2022 XXXII INTERNATIONAL SCIENTIFIC SYMPOSIUM METROLOGY AND METROLOGY ASSURANCE (MMA), 2022, : 120 - 124
  • [43] AN EFFICIENT METHOD FOR OBTAINING SIMILARITY DATA
    GOLDSTONE, R
    BEHAVIOR RESEARCH METHODS INSTRUMENTS & COMPUTERS, 1994, 26 (04): : 381 - 386
  • [44] Software Defect Prediction Based on Stability Test Data
    Okumoto, Kazu
    2011 INTERNATIONAL CONFERENCE ON QUALITY, RELIABILITY, RISK, MAINTENANCE, AND SAFETY ENGINEERING (ICQR2MSE), 2011, : 385 - 387
  • [45] Finding Focused Itemsets from Software Defect Data
    Zafar, Hafsa
    Rana, Zeeshan
    Shamail, Shafay
    Awais, Mian M.
    2012 15TH INTERNATIONAL MULTITOPIC CONFERENCE (INMIC), 2012, : 418 - 423
  • [46] Feature Selection with Imbalanced Data for Software Defect Prediction
    Khoshgoftaar, Taghi M.
    Gao, Kehan
    EIGHTH INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND APPLICATIONS, PROCEEDINGS, 2009, : 235 - +
  • [47] Imbalanced Data Processing Model for Software Defect Prediction
    Lijuan Zhou
    Ran Li
    Shudong Zhang
    Hua Wang
    Wireless Personal Communications, 2018, 102 : 937 - 950
  • [48] A Systematic Data Collection Procedure for Software Defect Prediction
    Mausa, Goran
    Grbac, Tihana Galinac
    Basic, Bojana Dalbelo
    COMPUTER SCIENCE AND INFORMATION SYSTEMS, 2016, 13 (01) : 173 - 197
  • [49] Imbalanced Data Processing Model for Software Defect Prediction
    Zhou, Lijuan
    Li, Ran
    Zhang, Shudong
    Wang, Hua
    WIRELESS PERSONAL COMMUNICATIONS, 2018, 102 (02) : 937 - 950
  • [50] Research on Software Defect Prediction Based on Data Mining
    Chen, Yuan
    Shen, Xiang-heng
    Du, Peng
    Ge, Bing
    2010 2ND INTERNATIONAL CONFERENCE ON COMPUTER AND AUTOMATION ENGINEERING (ICCAE 2010), VOL 1, 2010, : 563 - 567
12345