Proceedings of the 2016 4th International Conference on Machinery, Materials and Information Technology Applications

DT : a detection tool to automatically detect code smell in software project

Authors
Xinghua Liu, Cheng Zhang
Corresponding Author
Xinghua Liu
Available Online January 2017.
DOI
https://doi.org/10.2991/icmmita-16.2016.126How to use a DOI?
Keywords
code smell; detection; detection tool; metric; threshold
Abstract

Context: Code smell can make the decline of code quality. Code smell is not a bug, and also can't make system to run exceptionally. It just can make some difficulties for software developers to understand and maintain the source code of projects, and then cause unnecessary maintenance costs. Objective: We try to more accurately detect code smell. Method: We put forward our smell detection tool: DT for short. We use DT to detect eleven code smells through detecting two kinds of projects: lab project, industrial project. Result: We get good results by using our Smell Detection Tool (DT), comparing with some famous detection tools: Checkstyle, PMD, JDeodorant and iPlasma. Conclusion: Our method Smell Detection Tool (DT) can be used to detect 11 kinds of code smell, In the future, we will go on detecting more code smells that can't be detected, and then do a survey about code smell among the software developers and maintainers.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2016 4th International Conference on Machinery, Materials and Information Technology Applications
Series
Advances in Computer Science Research
Publication Date
January 2017
ISBN
978-94-6252-285-5
ISSN
2352-538X
DOI
https://doi.org/10.2991/icmmita-16.2016.126How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Xinghua Liu
AU  - Cheng Zhang
PY  - 2017/01
DA  - 2017/01
TI  - DT : a detection tool to automatically detect code smell in software project
BT  - Proceedings of the 2016 4th International Conference on Machinery, Materials and Information Technology Applications
PB  - Atlantis Press
SP  - 681
EP  - 684
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmmita-16.2016.126
DO  - https://doi.org/10.2991/icmmita-16.2016.126
ID  - Liu2017/01
ER  -