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Paper Details
Paper Title
A Methodology for Evaluation and Prediction of Defect-Proneness in Software
Authors
  Silpa.C,  Dr.K.Ramani,  Jahnavi.K
Abstract
Predicting defect-prone software components is an economically important activity. Software defect prediction work focuses on three ways 1) Estimating the number of defects remaining in software systems, 2) Discovering defect associations, and 3) Classifying the defect proneness of software components. The software defect prediction that supports both unbiased and comprehensive comparison between competing prediction systems. This methodology is comprised of 1) scheme evaluation and 2) defect prediction components. The scheme evaluation analyzes the prediction performance of competing learning schemes for given historical data sets. The defect predictor builds models according to the evaluated learning scheme and predicts software defects with new data according to the constructed model. In the evaluation stage different learning schemes are evaluated and best one is selected. In the prediction stage the best learning scheme is used to build a predictor with all historical data and the predictor is finally used to predict defect on new data. This system classifies the defect-proneness of software components into two classes, defect-prone and non defect-Prone.
Keywords- Scheme evaluation, Software defect prediction, Software defect-proneness prediction, Historical data, Learning schemes.
Publication Details
Unique Identification Number - IJEDRCP1403031Page Number(s) - 152-156Pubished in - Volume 2 | Issue NCETSE Conference | March 2014DOI (Digital Object Identifier) -    Publisher - IJEDR (ISSN - 2321-9939)
Cite this Article
  Silpa.C,  Dr.K.Ramani,  Jahnavi.K,   "A Methodology for Evaluation and Prediction of Defect-Proneness in Software", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.2, Issue NCETSE Conference, pp.152-156, March 2014, Available at :http://www.ijedr.org/papers/IJEDRCP1403031.pdf
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