HBSNIFF: A static analysis tool for Java']Java Hibernate object-relational mapping code smell detection

被引：4
|
作者：
Huang, Zijie [1 ]
Shao, Zhiqing [1 ]
Fan, Guisheng [1 ]
Yu, Huiqun [1 ]
Yang, Kang [1 ]
Zhou, Ziyi [1 ]
机构：
[1] East China Univ Sci & Technol, Dept Comp Sci & Engn, Shanghai 200237, Peoples R China
来源：
SCIENCE OF COMPUTER PROGRAMMING | 2022年 / 217卷
基金：
上海市自然科学基金; 中国国家自然科学基金;
关键词：
Code smell; Object-relational mapping; Hibernate; Static analysis; Object-oriented programming; IMPACT;
D O I：
10.1016/j.scico.2022.102778
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
Code smells are symptoms of sub-optimal software design and implementation choices. Detection tools were actively developed for general code smell related to coupling and cohesion issues, but such tools cannot capture domain-specific problems. In this work, we fill the gap in data persistence and query code quality by proposing HBSNIFF, i.e., a static analysis tool for detecting 14 code smells as well as 4 mapping metrics in Java Hibernate Object-Relational Mapping (ORM) codes. HBSNIFF is tested, documented, and manually validated. It also generates readable and customizable reports for every project. Moreover, it is beneficial to Mining Software Repository (MSR) research requiring large-scale analysis since project compilation is not needed for detection. (c) 2022 Elsevier B.V. All rights reserved.
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页数：10
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