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A Novel Approach for Software Defect prediction Based on the Power Law Function

Junhua Ren, Feng Liu
2020 Applied Sciences  
The proposed approach is thus demonstrated to be feasible and highly efficient at software defect prediction with unlabeled datasets.  ...  In this study, we proposed a novel approach that adopts power law function characteristics for software defect prediction.  ...  defect prediction in unlabeled instances.  ... 
doi:10.3390/app10051892 fatcat:kuphglo6knhwhi2cqi7wgr22oq

Revisiting Heterogeneous Defect Prediction: How Far Are We? [article]

Xiang Chen, Yanzhou Mu, Chao Ni, Zhanqi Cui
2019 arXiv   pre-print
Then, we perform diversity analysis on defective modules via McNemar's test and find the prediction diversity is more obvious when the comparison is performed between the HDP methods and the unsupervised  ...  Until now, researchers have proposed several novel heterogeneous defect prediction HDP methods with promising performance.  ...  the Actual Type and Predicted Type of Program Modules Actual Program Type Predicted Program Type Defective modules Non-defective modules Defective modules T P F N Non-defective modules F P T N  ... 
arXiv:1908.06560v1 fatcat:ocx47kcftbckvd6a66ppfl2e2i

A Systematic Review of Unsupervised Learning Techniques for Software Defect Prediction [article]

Ning Li, Martin Shepperd, Yuchen Guo
2020 arXiv   pre-print
Unsupervised machine learners have been increasingly applied to software defect prediction.  ...  Objective: Investigate the use and performance of unsupervised learning techniques in software defect prediction.  ...  Although there are small variants in the five search engines, our key search string is: ("fault prediction" OR "defect prediction" OR "bug prediction" OR "error prediction") AND ("unsupervised" OR "unlabel  ... 
arXiv:1907.12027v4 fatcat:q2o5ew5zhra5lauyebd3hl65uy

Software defect prediction based on stacked sparse denoising autoencoders and enhanced extreme learning machine

Nana Zhang, Shi Ying, Kun Zhu, Dandan Zhu
2021 IET Software  
To address these two issues, a novel defect prediction model called SSEPG based on Stacked Sparse Denoising AutoEncoders (SSDAE) and Extreme Learning Maching (ELM) optimised by Particle Swarm Optimisation  ...  Software defect prediction is an important software quality assurance technique.  ...  [30] proposed an unsupervised defect prediction model named CLAMI on unlabelled datasets by using an automated manner.  ... 
doi:10.1049/sfw2.12029 fatcat:225jhgnn6nebra7fh6fxcucqpe

Predictive Models in Software Engineering: Challenges and Opportunities [article]

Yanming Yang, Xin Xia, David Lo, Tingting Bi, John Grundy, Xiaohu Yang
2020 arXiv   pre-print
Predictive models are one of the most important techniques that are widely applied in many areas of software engineering.  ...  This paper is a first attempt to systematically organize knowledge in this area by surveying a body of 139 papers on predictive models.  ...  [95] proposed novel approaches CLA and CLAMI, which can work well for defect prediction on unlabeled datasets in an automated manner without any manual effort. Gong et al.  ... 
arXiv:2008.03656v1 fatcat:fe7ylphujfbobeo3g5yevniiei