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@article{143210,
        author = {Margi Patel},
        title = {A Survey on Software Fault Prediction Technique based on Clustering Algorithm and Artificial Intelligence},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {2},
        number = {7},
        pages = {623-627},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=143210},
        abstract = {There has been rapid growth of software development. During Transmission of Data faults are Created. However software Fault Prediction Techniques are used to Detect Fault. Software Fault Prediction improve the quality and reliability of software by predicting faults .Quality of Software measure in term of fault proneness of data .These software defect may lead to degradation of the quality which might be the cause of failure. In this paper focus on clustering with large dataset and predicting faults efficiently. We show a comparatively analysis of software fault prediction based on clustering technique, neural network method, statistical method. Fault prediction reduce the overall time and less data processing.},
        keywords = {Fault Prediction, Clustering Technique, Neural Network Technique, Statistical method},
        month = {},
        }