Software Defect Prediction using Efficient Classification Algorithms
Anju A. J1, J. E. Judith2
1Anju A. J, Research Scholar, Department of Computer Science Engineering, Noorul Islam Center For Higher Eductaion, Kumaracovil (Tamil Nadu), India.
2J. E. Judith, Associate Professor, Department of Computer Science Engineering, Noorul Islam Center For Higher Eductaion, Kumaracovil (Tamil Nadu), India.
Manuscript received on 19 November 2019 | Revised Manuscript received on 04 December 2019 | Manuscript Published on 10 December 2019 | PP: 301-304 | Volume-8 Issue-3S2 October 2019 | Retrieval Number: C10581083S219/2019©BEIESP | DOI: 10.35940/ijrte.C1058.1083S219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The reliability of the software can be understood using the recurrence and the development of failures or it could be recognized by framework accessibility. Software can be classified as many forms such as system software, application software, shareware, literate, freeware public domain etc. Nearly, all the frameworks used to have faults and these faults results in the failure. Inorder to understand these faults, some software fault prediction is used. The main aim of these method is to predict the errors and their cause before it occurs. This article mainly discusses about the techniques which are available for the prediction of error and gives the information to understand about the data mining with NASA MDP data sets.
Keywords: Algorithm, Data Mining, Defect Prediction, Application Softwares.
Scope of the Article: Classification