2013
DOI: 10.5120/12903-9587
|View full text |Cite
|
Sign up to set email alerts
|

Cross Company and within Company Fault Prediction using Object Oriented Metrics

Abstract: This paper investigates fault predictions in the cross-project context focusing on the object oriented metrics for the organizations that do not track fault related data. In this study, empirical analysis is carried out to validate object-oriented Chidamber and Kemerer (CK) design metrics for cross project fault prediction. The machine learning techniques used for evaluation are J48, NB, SVM, RF, K-NN and DT. The results indicate CK metrics can be used as initial guideline for the projects where no previous fa… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2

Citation Types

0
3
0

Year Published

2017
2017
2024
2024

Publication Types

Select...
3
2
1

Relationship

0
6

Authors

Journals

citations
Cited by 9 publications
(3 citation statements)
references
References 18 publications
0
3
0
Order By: Relevance
“…He et al (2018) proposed a Transfer Component Analysis (TCA) based model for cross-project defect prediction, which aims to align the distributions of source and target projects to improve the transferability of predictive models [8]. Singh et al (2013) explored cross-company and withincompany fault prediction using object-oriented metrics. Their study demonstrated that models built on data from other companies could be successfully applied to predict defects in a target company [14].…”
Section: Cross-project Prediction For Software Fault Predictionmentioning
confidence: 99%
See 1 more Smart Citation
“…He et al (2018) proposed a Transfer Component Analysis (TCA) based model for cross-project defect prediction, which aims to align the distributions of source and target projects to improve the transferability of predictive models [8]. Singh et al (2013) explored cross-company and withincompany fault prediction using object-oriented metrics. Their study demonstrated that models built on data from other companies could be successfully applied to predict defects in a target company [14].…”
Section: Cross-project Prediction For Software Fault Predictionmentioning
confidence: 99%
“…Singh et al (2013) explored cross-company and withincompany fault prediction using object-oriented metrics. Their study demonstrated that models built on data from other companies could be successfully applied to predict defects in a target company [14]. Xia et al (2016) introduced the Hybrid model reconstruction approach (HYDRA), a compositional model for cross-project defect prediction.…”
Section: Cross-project Prediction For Software Fault Predictionmentioning
confidence: 99%
“…4.24 Singh et al, 2013 Approach Singh et al (2013). do not propose any special approach, but evaluate pair-wise prediction without additional data treatment.…”
mentioning
confidence: 99%