RETRACTED ARTICLE: Exponential Relationship Based Approach for Predictions of Defect Density Using Optimal Module Sizes

  • Dinesh Kumar Verma
  • Shishir KumarEmail author
Research Article


Although, a number of researches have been taken to predict software defect density, analysis of dependency of this attribute on particular factor is need of researchers. In the recent time, software industries applying more efforts in the testing, for identifying and fixing the bugs early in the software development process. Software defect density is considered as the parameter validating the readiness of software product before release. Using this parameter, developers can identify the possibilities of improvements in the product. Most of the projects reflect a dependency of defect density on the size of the modules. The nature of dependency, need to be analyzed for better prediction of defect density. In this paper analyzed with optimal values of parameters by considering the logarithmic nature of dependency. These optimal values of parameter gave a better prediction of defect density by varying in module sizes. Analysis of the proposed model was performed on the available data sets and compared with the model given by Verma and Kumar. The curve fitting method was used to drive the optimal values of parameters. At the end it inferred that the prediction of defect density could be optimized by effective distribution of size of modules. The exponential relationship between module size and defect density give more optimized defect density.


Module Size Defect density Min–max criteria Method of least square Curve fitting 


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Copyright information

© The National Academy of Sciences, India 2016

Authors and Affiliations

  1. 1.Department of Computer ScienceJaypee University of Engineering and TechnologyGunaIndia

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