CFP last date
20 December 2024
Call for Paper
January Edition
IJCA solicits high quality original research papers for the upcoming January edition of the journal. The last date of research paper submission is 20 December 2024

Submit your paper
Know more
The week's pick
Responsive image
Improved Shuffled Frog Leaping Algorithm with Self-Adaptive Shuffling for Fuzzy Logic PD+G Controller Optimization in Robotic Manipulators

Duc Hoang Nguyen
Random Articles
Reseach Article

Analysis of CK Metrics to Predict Software Fault-Proneness using Bayesian Inference

by Heena Kapila, Satwinder Singh
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 74 - Number 2
Year of Publication: 2013
Authors: Heena Kapila, Satwinder Singh
10.5120/12854-9152

Heena Kapila, Satwinder Singh . Analysis of CK Metrics to Predict Software Fault-Proneness using Bayesian Inference. International Journal of Computer Applications. 74, 2 ( July 2013), 1-4. DOI=10.5120/12854-9152

@article{ 10.5120/12854-9152,
author = { Heena Kapila, Satwinder Singh },
title = { Analysis of CK Metrics to Predict Software Fault-Proneness using Bayesian Inference },
journal = { International Journal of Computer Applications },
issue_date = { July 2013 },
volume = { 74 },
number = { 2 },
month = { July },
year = { 2013 },
issn = { 0975-8887 },
pages = { 1-4 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume74/number2/12854-9152/ },
doi = { 10.5120/12854-9152 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:41:08.046544+05:30
%A Heena Kapila
%A Satwinder Singh
%T Analysis of CK Metrics to Predict Software Fault-Proneness using Bayesian Inference
%J International Journal of Computer Applications
%@ 0975-8887
%V 74
%N 2
%P 1-4
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The fault prediction model grants assistance during the software development by providing recourse to the present faults with the Bayesian Interference. All faults prediction techniques get a help in this study with the designing of Logistic regression model and Bayesian inference altogether. It is also told as fact that Bayesian inference graph can be represented for probabilistic approach for the faults both presented and identified for the upcoming release. For Probabilistic reliability analysis, Bayesian inference is intended to be evaluated for risk related data. These findings suggest that there is a relationship between faulty classes and object-oriented metrics. This study demonstrates as the performance evaluation technique for any piece of software. We examine the open source Eclipse system, which has a strong industrial usage. The focus of the study is to design Bayesian Inference graph and predict faults for next piece of software.

References
  1. Raed Shatnawi1, Wei Li, James Swain," Finding software metrics threshold values using ROC curves" , JOURNAL OF SOFTWARE MAINTENANCE AND EVOLUTION: RESEARCH AND PRACTICE, Evol. : Res. Pract. 2010; 22:1–16
  2. Ganesh J. Pai, Member, IEEE, and Joanne Bechta Dugan ," Empirical Analysis of Software Fault Content and Fault Proneness Using Bayesian Methods",IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, VOL. 33, NO. 10, OCTOBER 2007
  3. Satwinder Singh and K. S. Kahlon ," Effectiveness of Encapsulation and Object-oriented Metrics to Refactor Code and Identify Error Prone Classes using Bad Smells", ACM SIGSOFT Software Engineering Notes Volume 36, Number 5,September 2011
  4. C. Catal, U. Sevim, and B. Diri, Member, IAENG"Software Fault Prediction of Unlabeled Program Modules" Proceedings of the World Congress on Engineering 2009 Vol I WCE 2009, July 1 - 3, 2009,London, U. K
  5. Norman Fenton , Martin Neil , William Marsh , Peter Hearty , David Marquez , Paul Krause , Rajat Mishra,"Predicting software defects in varying development lifecycles using Bayesian nets", Information and Software Technology 49 (2007) 32–43
  6. Ramanath Subramanyam and M. S. Krishnan,"Empirical Analysis of CK Metrics for Object-Oriented Design Complexity: Implications for Software Defects" IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, VOL. 29, NO. 4, APRIL 2003
  7. Shyam R. Chidamber and Chris F. Kemerer, "A Metrics Suite for Object Oriented Design," IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, VOL. 20, NO. 6, JUNE 1994.
  8. V. R. Basili, L. C. Briand, and W. L. Melo, "A Validation of Object- Oriented Design Metrics as Quality Indicators," IEEE Trans. Software Eng. , vol. 22, no. 10, pp. 751-761, Oct. 1996.
  9. . T. R. Gopalakrishnan Nair, R. Selvarani," Defect proneness estimation and feedback approach for software design quality improvement", Information and Software Technology 54 (2012) 274–285
  10. Shyam R. Chidamber, David P. Darcy, and Chris F. Kemerer, "Managerial Use of Metrics for Object-Oriented Software: An Exploratory Analysis," IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, VOL. 24, NO. 8, AUGUST 1998
  11. Hector M. Olague, Letha H. Etzkorn, Senior Member, IEEE, Sampson Gholston, and cxStephen Quattlebaum, " Empirical Validation of Three Software Metrics Suites to Predict Fault-Proneness of Object-Oriented Classes Developed Using Highly Iterative or Agile Software Development Processes"
  12. Mohammad Alshayeb, Member and Wei Li,"An Empirical Validation of Object-Oriented Metrics in Two Different Iterative Software Processes" , IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, VOL. 29, NO. 11, NOVEMBER 2003
  13. Jiang, Y. , Cukic, B. , Ma, Y. , 2008. Techniques for evaluating fault prediction models. Empirical Software Engineering 13 (5), 561–595.
  14. R. Bender, "Quantitative Risk Assessment in Epidemiological Studies Investigating Threshold Effects," Biometrical J. , vol. 41,no. 3, pp. 305-319, 1999.
  15. Raed Shatnawi," A Quantitative Investigation of the Acceptable Risk Levels of Object-Oriented Metrics in Open-Source Systems" IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, VOL. 36, NO. 2, MARCH/APRIL 2010
  16. Tibor Gyimo´ thy, Rudolf Ferenc, and Istva´n Siket," Empirical Validation of Object-Oriented Metricson Open Source Software for Fault Prediction", IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, VOL. 31, NO. 10, OCTOBER 2005
  17. Analyst4j," http://www. codeswat. com"
  18. Karel Dejaeger,Thomas Verbraken,Bart Baesens ,"Toward Comprehensible Software Fault Prediction Models Using Bayesian Network Classifiers" IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, VOL. 39, NO. 2, FEBRUARY 2013
  19. Dr. Linda H. Rosenberg," Applying and Interpreting Object Oriented Metrics"
  20. Bayesian Inference Concepts, "http://www. epixanalytics. com"
Index Terms

Computer Science
Information Sciences

Keywords

Bayesian Inference Fault Prediction Software reliability CK metrics

Powered by PhDFocusTM