The effect of the dataset size on the accuracy of software defect prediction models: An empirical study

被引：0
|
作者：
Alshammari, Mashaan A. [1 ]
Alshayeb, Mohammad [2 ]
机构：
[1] Information and Computer Science Department, University of Ha'il, Ha'il, Saudi Arabia
[2] Information and Computer Science Department, Interdisciplinary Research Center for, Intelligent Secure Systems, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia
来源：
Inteligencia Artificial | 2021年 / 24卷 / 68期
关键词：
D O I：
暂无
中图分类号：
学科分类号：
摘要：
引用
收藏
页码：72 / 88
相关论文
共 50 条
  • [21] The Performance Stability of Defect Prediction Models with Class Imbalance: An Empirical Study
    Yu, Qiao
    Jiang, Shujuan
    Zhang, Yanmei
    IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, 2017, E100D (02) : 265 - 272
  • [22] The Impact Study of Class Imbalance on the Performance of Software Defect Prediction Models
    Yu Q.
    Jiang S.-J.
    Zhang Y.-M.
    Wang X.-Y.
    Gao P.-F.
    Qian J.-Y.
    Qian, Jun-Yan (qjy2000@gmail.com), 2018, Science Press (41): : 809 - 824
  • [23] On the dataset shift problem in software engineering prediction models
    Burak Turhan
    Empirical Software Engineering, 2012, 17 : 62 - 74
  • [24] On the dataset shift problem in software engineering prediction models
    Turhan, Burak
    EMPIRICAL SOFTWARE ENGINEERING, 2012, 17 (1-2) : 62 - 74
  • [25] Assessing effort prediction models for corrective software maintenance - An empirical study
    De Lucia, Andrea
    Pompella, Eugenio
    Stefanucci, Silvio
    ENTERPRISE INFORMATION SYSTEMS VI, 2006, : 55 - +
  • [26] An empirical study toward dealing with noise and class imbalance issues in software defect prediction
    Pandey, Sushant Kumar
    Tripathi, Anil Kumar
    SOFT COMPUTING, 2021, 25 (21) : 13465 - 13492
  • [27] An Empirical Study for Enhanced Software Defect Prediction Using a Learning-Based Framework
    Kamal Bashir
    Tianrui Li
    Chubato Wondaferaw Yohannese
    International Journal of Computational Intelligence Systems, 2018, 12 : 282 - 298
  • [28] An Empirical Study on Application of Word Embedding Techniques for Prediction of Software Defect Severity Level
    Kumar, Lov
    Kumar, Mukesh
    Murthy, Lalita Bhanu
    Misra, Sanjay
    Kocher, Vipul
    Padmanabhuni, Srinivas
    PROCEEDINGS OF THE 2021 16TH CONFERENCE ON COMPUTER SCIENCE AND INTELLIGENCE SYSTEMS (FEDCSIS), 2021, : 477 - 484
  • [29] An empirical study of data sampling techniques for just-in-time software defect prediction
    Li, Zhiqiang
    Du, Qiannan
    Zhang, Hongyu
    Jing, Xiao-Yuan
    Wu, Fei
    AUTOMATED SOFTWARE ENGINEERING, 2024, 31 (02)
  • [30] An empirical study toward dealing with noise and class imbalance issues in software defect prediction
    Sushant Kumar Pandey
    Anil Kumar Tripathi
    Soft Computing, 2021, 25 : 13465 - 13492
12345