Details

Autor(en) / Beteiligte

• Huang, Zijie
• Shao, Zhiqing
• Fan, Guisheng
• Yu, Huiqun
• Yang, Kang
• Zhou, Ziyi

Titel

HBSniff: A static analysis tool for Java Hibernate object-relational mapping code smell detection

Ist Teil von

• Science of computer programming, 2022-05, Vol.217, p.102778, Article 102778

Ort / Verlag

Elsevier B.V

Erscheinungsjahr

2022

Quelle

Access via ScienceDirect (Elsevier)

Beschreibungen/Notizen

• •No project compilation needed for detection.•14 detectable smells.•4 implemented mapping metrics.•Excel report visualization. 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.