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Improved Software Fault Prediction using Bayesian Network Classifier

J. Christy Paulin, S. Tamilarasi

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.

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References


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