UGC Approved Journal no 63975

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 6 Issue 6
June-2019
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIRCO06032


Registration ID:
216231

Page Number

162-168

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Title

Defect Prediction by Analysing Software Project Reports Using Logistic Regression

Authors

Abstract

The large and complex software in today’s scenario has led to unavoidable circumstances wherein defects are entering the system at an enormous rate. This has caused an emerging need to assess the severity of these defects considering the shortage of resources due to which equal amount of resources cannot be allocated to all the defects. Thus, in this paper, we intend to propose a model that will be used to assess the severity level of the defect introduced in the system so that defects having higher priority can be dealt with utmost attention. The model is validated against an open source NASA dataset of PITS database using a learning based technique namely Multinominal Multivariate Logistic Regression (MMLR). A series of text mining techniques were applied for pre-processing the data. Finally, validation of the data was conducted using Receiver Operating Characteristics (ROC) characterstics.

Key Words

Receiver Operating Characteristics, Text mining, Defect, Severity, Multinominal Multivariate Logistic Regression

Cite This Article

"Defect Prediction by Analysing Software Project Reports Using Logistic Regression", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.162-168, June-2019, Available :http://www.jetir.org/papers/JETIRCO06032.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Defect Prediction by Analysing Software Project Reports Using Logistic Regression", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp162-168, June-2019, Available at : http://www.jetir.org/papers/JETIRCO06032.pdf

Publication Details

Published Paper ID: JETIRCO06032
Registration ID: 216231
Published In: Volume 6 | Issue 6 | Year June-2019
DOI (Digital Object Identifier):
Page No: 162-168
Country: Bikaner, Rajasthan, India .
Area: Engineering
ISSN Number: 2349-5162


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