Software Technology Research
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App. Res. of Comp. Printed Article
Vol. 38, 2021 No. 6
1815-1818

ORESP: software defect severity prediction based on ordinal regression

Jia Yanxin1
Chen Xiang1,2
Ge Hua1
Yang Guang1
Lin Hao1
1. School of Information Science & Technology, Nantong University, Nantong Jiangsu 226019, China
2. State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210023, China
DOI: 10.19734/j.issn.1001-3695.2020.07.0249

Abstract

To improve the prediction performance of the severity of software defects, considering the order between different labels, this paper proposed a defect severity prediction method ORESP based on ordinal regression. This method used the Spearman-based feature selection method to identify and remove redundant features in the data set and then used a neural network based on the proportional odds model to build prediction models. By comparing with the five classical classification methods, the proposed method ORESP could achieve better prediction performance under four different categories of module metrics. In terms of MZE(average zero-one error) measure, the performance of the proposed model can be improved by 10.3% at most; in terms of MAE(mean absolute error), the performance of the proposed model can be improved by 12.3% at most. In addition, using the feature selection method based on Spearman can effectively improve the prediction performance of ORESP.

Foundation Support

国家自然科学基金资助项目(61702041)
南京大学计算机软件新技术国家重点实验室开放课题(KFKT2019B14)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2020.07.0249
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 6
Section: Software Technology Research
Pages: 1815-1818
Serial Number: 1001-3695(2021)06-040-1815-04

Publish History

[2021-06-05] Printed Article

Cite This Article

贾焱鑫, 陈翔, 葛骅, 等. ORESP：基于有序回归的软件缺陷严重程度预测方法 [J]. 计算机应用研究, 2021, 38 (6): 1815-1818. (Jia Yanxin, Chen Xiang, Ge Hua, et al. ORESP: software defect severity prediction based on ordinal regression [J]. Application Research of Computers, 2021, 38 (6): 1815-1818. )

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  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

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