Skip to content
Publish & Distribute
Publishing Solutions
Distribution Solutions
Library Services
Subjects
Architecture and Design
Arts
Business and Economics
Chemistry
Classical and Ancient Near Eastern Studies
Computer Sciences
Cultural Studies
Engineering
General Interest
Geosciences
History
Industrial Chemistry
Jewish Studies
Law
Library and Information Science, Book Studies
Life Sciences
Linguistics and Semiotics
Literary Studies
Materials Sciences
Mathematics
Medicine
Music
Pharmacy
Philosophy
Physics
Social Sciences
Sports and Recreation
Theology and Religion
Publications
Journals
Books
Proceedings
Publishers
Journal Matcher
Blog
Contact
Search
English
English
Deutsch
Polski
Español
Français
Italiano
Cart
Home
Journals
Foundations of Computing and Decision Sciences
Volume 47 (2022): Issue 1 (February 2022)
Open Access
ANN Modelling on Vulnerabilities Detection in Code Smells-Associated Android Applications
Aakanshi Gupta
Aakanshi Gupta
ASET, GGSIPU
New Delhi, India
Search for this author on
Sciendo
|
Google Scholar
Gupta, Aakanshi
,
Deepanshu Sharma
Deepanshu Sharma
Executive Branch-IT, Indian Navy
Search for this author on
Sciendo
|
Google Scholar
Sharma, Deepanshu
and
Kritika Phulli
Kritika Phulli
Application Development Associate
Accenture, India
Search for this author on
Sciendo
|
Google Scholar
Phulli, Kritika
Feb 23, 2022
Foundations of Computing and Decision Sciences
Volume 47 (2022): Issue 1 (February 2022)
About this article
Previous Article
Next Article
Abstract
References
Authors
Articles in this Issue
Preview
PDF
Cite
Share
Download Cover
Published Online:
Feb 23, 2022
Page range:
3 - 26
Received:
Jan 15, 2021
Accepted:
Sep 30, 2021
DOI:
https://doi.org/10.2478/fcds-2022-0001
Keywords
Software Vulnerabilities
,
Code Smells
,
Android
,
ANN
,
Apriori Algorithm
,
Deep Learning
,
Machine Learning
© 2022 Aakanshi Gupta et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.
