CloudScent: a model for code smell analysis in open-source cloud
- URL: http://arxiv.org/abs/2307.12146v1
- Date: Sat, 22 Jul 2023 19:01:38 GMT
- Title: CloudScent: a model for code smell analysis in open-source cloud
- Authors: Raj Narendra Shah, Sameer Ahmed Mohamed, Asif Imran, Tevfik Kosar
- Abstract summary: We propose a model called CloudScent which is an open source mechanism to detect smells in open-source cloud.
Results show that CloudScent is capable of accurately detecting 8 code smells in cloud.
- Score: 2.990411348977783
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: The low cost and rapid provisioning capabilities have made open-source cloud
a desirable platform to launch industrial applications. However, as open-source
cloud moves towards maturity, it still suffers from quality issues like code
smells. Although, a great emphasis has been provided on the economic benefits
of deploying open-source cloud, low importance has been provided to improve the
quality of the source code of the cloud itself to ensure its maintainability in
the industrial scenario. Code refactoring has been associated with improving
the maintenance and understanding of software code by removing code smells.
However, analyzing what smells are more prevalent in cloud environment and
designing a tool to define and detect those smells require further attention.
In this paper, we propose a model called CloudScent which is an open source
mechanism to detect smells in open-source cloud. We test our experiments in a
real-life cloud environment using OpenStack. Results show that CloudScent is
capable of accurately detecting 8 code smells in cloud. This will permit cloud
service providers with advanced knowledge about the smells prevalent in
open-source cloud platform, thus allowing for timely code refactoring and
improving code quality of the cloud platforms.
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