Intelligent radar software defect classification approach based on the latent Dirichlet allocation topic model

EURASIP Journal on Advances in Signal Processing

Jiabin Chen¹  Shengli Wang¹  Xi Liu¹  Chang Liu²  Haifeng Li²  Rui Yin³  Yongfeng Yin³ 

[1] Nanjing Research Institute of Electronics Technology, 210013, Nanjing, China;School of Reliability and Systems Engineering, Beihang University, 100191, Beijing, China;School of Software, Beihang University, 100191, Beijing, China;

关键词: Radar software;    Software defect;    Defect classification;    Latent Dirichlet allocation (LDA) topic model;   

DOI  :  10.1186/s13634-021-00761-3

来源: Springer

【 摘 要 】

Existing software intelligent defect classification approaches do not consider radar characters and prior statistics information. Thus, when applying these appaoraches into radar software testing and validation, the precision rate and recall rate of defect classification are poor and have effect on the reuse effectiveness of software defects. To solve this problem, a new intelligent defect classification approach based on the latent Dirichlet allocation (LDA) topic model is proposed for radar software in this paper. The proposed approach includes the defect text segmentation algorithm based on the dictionary of radar domain, the modified LDA model combining radar software requirement, and the top acquisition and classification approach of radar software defect based on the modified LDA model. The proposed approach is applied on the typical radar software defects to validate the effectiveness and applicability. The application results illustrate that the prediction precison rate and recall rate of the poposed approach are improved up to 15 ~ 20% compared with the other defect classification approaches. Thus, the proposed approach can be applied in the segmentation and classification of radar software defects effectively to improve the identifying adequacy of the defects in radar software.

【 授权许可】

CC BY