Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

Improved Software Fault Prediction Using Bayesian Network Classifier


Affiliations
1 Shivani Engineering College, Trichy, India
2 Department of Computer Science, Shivani Engineering College, Trichy, India
     

   Subscribe/Renew Journal


Software Fault Prediction model, which gives a forthright implication of flaw in a code. An auspicious sign of flaw inclined code will permit more effective and enhance by and large programming quality. Prediction model in which help to predict the fault from the coding. The various technique used to analyse is preprocessing, Markov Blanket Selection Model and Bayesian Network classifer. In this paper, we study about the techniques. Based on the selection of attributes we would help to find the fault. Software fault that are caused in the code will reduce the quality of the application. When the qualities are reduced the software will lose its value hence we go for the prediction of coding at each stage. This study will help to know more about the prediction process.

Keywords

Bayesian Network, Preprocessing, Markov Blanket Rule, H-Measure.
User
Subscription Login to verify subscription
Notifications
Font Size

Abstract Views: 179

PDF Views: 3




  • Improved Software Fault Prediction Using Bayesian Network Classifier

Abstract Views: 179  |  PDF Views: 3

Authors

J. Christy Paulin
Shivani Engineering College, Trichy, India
S. Tamilarasi
Department of Computer Science, Shivani Engineering College, Trichy, India

Abstract


Software Fault Prediction model, which gives a forthright implication of flaw in a code. An auspicious sign of flaw inclined code will permit more effective and enhance by and large programming quality. Prediction model in which help to predict the fault from the coding. The various technique used to analyse is preprocessing, Markov Blanket Selection Model and Bayesian Network classifer. In this paper, we study about the techniques. Based on the selection of attributes we would help to find the fault. Software fault that are caused in the code will reduce the quality of the application. When the qualities are reduced the software will lose its value hence we go for the prediction of coding at each stage. This study will help to know more about the prediction process.

Keywords


Bayesian Network, Preprocessing, Markov Blanket Rule, H-Measure.