Pattern Mining-based Warning Prioritization by Refining Abstract Syntax Tree

IF 0.6 4区计算机科学 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

International Journal of Software Engineering and Knowledge Engineering Pub Date : 2024-06-07 DOI:10.1142/s0218194024500293

Xiuting Ge, Xuanye Li, Yuanyuan Sun, Mingshuang Qing, Haitao Zheng, Huibin Zhang, Xianyu Wu

引用次数: 0

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通过提炼抽象语法树确定基于模式挖掘的警告优先级

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Software Engineering and Knowledge Engineering 工程技术-工程：电子与电气

CiteScore

1.90

自引率

11.10%

发文量

审稿时长

16 months

期刊介绍： The International Journal of Software Engineering and Knowledge Engineering is intended to serve as a forum for researchers, practitioners, and developers to exchange ideas and results for the advancement of software engineering and knowledge engineering. Three types of papers will be published: Research papers reporting original research results Technology trend surveys reviewing an area of research in software engineering and knowledge engineering Survey articles surveying a broad area in software engineering and knowledge engineering In addition, tool reviews (no more than three manuscript pages) and book reviews (no more than two manuscript pages) are also welcome. A central theme of this journal is the interplay between software engineering and knowledge engineering: how knowledge engineering methods can be applied to software engineering, and vice versa. The journal publishes papers in the areas of software engineering methods and practices, object-oriented systems, rapid prototyping, software reuse, cleanroom software engineering, stepwise refinement/enhancement, formal methods of specification, ambiguity in software development, impact of CASE on software development life cycle, knowledge engineering methods and practices, logic programming, expert systems, knowledge-based systems, distributed knowledge-based systems, deductive database systems, knowledge representations, knowledge-based systems in language translation & processing, software and knowledge-ware maintenance, reverse engineering in software design, and applications in various domains of interest.