Abstract
Software product's quality is one of the important aspects that affect the user, the developer, and the product. Measuring quality in the early phases of the project life cycle is a major goal of project planning. Accordingly, several research studies have been proposed to measure the software product quality attributes. In this paper, we empirically study the impact of afferent coupling (Ca), efferent coupling (Ce) and coupling between object (CBO) metrics on fault prediction using bivariate correlation. We built a prediction model using these metrics to predict faults by using multivariate logistic linear regression. A case study of an open source object oriented systems is used to evaluate the correlation between coupling metrics and faults.
Original language | English |
---|---|
Title of host publication | Proceedings of 2017 International Conference on Communication, Computing and Digital Systems, C-CODE 2017 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 211-215 |
Number of pages | 5 |
ISBN (Electronic) | 9781509044481 |
DOIs | |
State | Published - 3 May 2017 |
Publication series
Name | Proceedings of 2017 International Conference on Communication, Computing and Digital Systems, C-CODE 2017 |
---|
Bibliographical note
Publisher Copyright:© 2017 IEEE.
Keywords
- Afferent Coupling
- Efferent Coupling
- Fault Prediction
- Software Metrics
ASJC Scopus subject areas
- Computer Networks and Communications
- Computer Science Applications
- Computer Vision and Pattern Recognition
- Signal Processing