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Application of KNN Classification Technique in Detection of Software Fault

Ritika 1 , Er. Saurabh Sharma2

Section:Review Paper, Product Type: Journal Paper
Volume-7 , Issue-2 , Page no. 389-393, Feb-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i2.389393

Online published on Feb 28, 2019

Copyright © Ritika, Er. Saurabh Sharma . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Ritika, Er. Saurabh Sharma, “Application of KNN Classification Technique in Detection of Software Fault,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.2, pp.389-393, 2019.

MLA Style Citation: Ritika, Er. Saurabh Sharma "Application of KNN Classification Technique in Detection of Software Fault." International Journal of Computer Sciences and Engineering 7.2 (2019): 389-393.

APA Style Citation: Ritika, Er. Saurabh Sharma, (2019). Application of KNN Classification Technique in Detection of Software Fault. International Journal of Computer Sciences and Engineering, 7(2), 389-393.

BibTex Style Citation:
@article{Sharma_2019,
author = {Ritika, Er. Saurabh Sharma},
title = {Application of KNN Classification Technique in Detection of Software Fault},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {2 2019},
volume = {7},
Issue = {2},
month = {2},
year = {2019},
issn = {2347-2693},
pages = {389-393},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=3674},
doi = {https://doi.org/10.26438/ijcse/v7i2.389393}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i2.389393}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=3674
TI - Application of KNN Classification Technique in Detection of Software Fault
T2 - International Journal of Computer Sciences and Engineering
AU - Ritika, Er. Saurabh Sharma
PY - 2019
DA - 2019/02/28
PB - IJCSE, Indore, INDIA
SP - 389-393
IS - 2
VL - 7
SN - 2347-2693
ER -

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Abstract

The software engineering is the technology which is used to analyze software behavior SDP includes software metrics, their attributes like line of code etc. The main goal of software defects prediction model includes ordering new software modules based on their defect-proneness and classifying them whether it is new software or not. The main purpose of SDP for the ranking is to predict which modules have the most defects to define software quality enhancement. The goal of SDP for the ranking task is to predict the relative defect number, although estimating the precise number of defects of the modules is better than estimating the ranks of modules, because the precise number of defects can give more information than the ranks. The software defect prediction technique is applied in the previous work based on the technique of ANN. In this research work the technique of KNN is applied for the software defect prediction. It is analyzed that proposed technique has high accuracy and less execution time as compared to existing ANN technique.

Key-Words / Index Term

Fault Prediction, KNN, Software Defect Prediction, NFR ,ANN

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