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A Frame Work for Business Defect Predictions in Mobiles

by N. Gayatri, S. Nickolas, A. V. Reddy
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 81 - Number 1
Year of Publication: 2013
Authors: N. Gayatri, S. Nickolas, A. V. Reddy
10.5120/13979-1975

N. Gayatri, S. Nickolas, A. V. Reddy . A Frame Work for Business Defect Predictions in Mobiles. International Journal of Computer Applications. 81, 1 ( November 2013), 39-44. DOI=10.5120/13979-1975

@article{ 10.5120/13979-1975,
author = { N. Gayatri, S. Nickolas, A. V. Reddy },
title = { A Frame Work for Business Defect Predictions in Mobiles },
journal = { International Journal of Computer Applications },
issue_date = { November 2013 },
volume = { 81 },
number = { 1 },
month = { November },
year = { 2013 },
issn = { 0975-8887 },
pages = { 39-44 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume81/number1/13979-1975/ },
doi = { 10.5120/13979-1975 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:54:59.042738+05:30
%A N. Gayatri
%A S. Nickolas
%A A. V. Reddy
%T A Frame Work for Business Defect Predictions in Mobiles
%J International Journal of Computer Applications
%@ 0975-8887
%V 81
%N 1
%P 39-44
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Software quality is very highly inflammable area where enormous research has been done and still being continued for effective and exclusive product outcome. Identification of defects or issues in the early phase makes the system to rectify the issues earlier and helps to manage better product outcome within given budget and time which is ultimate goal of every company or project. The issues occurred while coding can be identified by the tools already developed. But if the issues occurred after delivery of the product cannot be identified before and these are called business defects, i. e. , while using the system defects occurs. This paper proposes a frame work for identifying the business defects and prediction for mobiles. The data used here is from Android mobiles. This frame work identifies the information, warnings, errors occurred while using the mobile. And also it gives the percentage of faulty status of the product if these errors occur regularly, so these issues can be rectified and corrected in the future developments of the product. Identification of business defects for mobile logs is the novelty of the paper.

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Index Terms

Computer Science
Information Sciences

Keywords

Mobile logs threshold defect prediction business defects

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