Identifying Code Quality Issues for Undergraduate Students Using Static Analysis and NLP

被引：0
|
作者：
Irnhmed, Essa [1 ]
Ceh-Varela, Edgar [1 ]
Kilgore, Scott [1 ]
机构：
[1] Eastern New Mexico Univ, Dept Math Sci, Portales, NM 88130 USA
来源：
2023 INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE AND COMPUTATIONAL INTELLIGENCE, CSCI 2023 | 2023年
关键词：
Coding Conventions; Static Code Analysis; CheckStyle; Natural Language Processing; Doc2Vec;
D O I：
10.1109/CSCI62032.2023.00252
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This study presents a detailed analysis of coding standards in the context of university-level programming courses. Focusing on the challenges faced by students in understanding and applying these standards, the study utilized the CheckStyle tool for Java programming and Natural Language Processing (NLP) techniques, such as Doc2Vec, for error categorization. The analysis revealed common issues, such as spacing problems and non-compliance with naming conventions, exacerbated by factors like tight schedules and limited grading emphasis. Importantly, this paper serves as an exploratory study utilizing advanced natural language processing methods, shedding light on students' complexities in adhering to coding standards.
引用
收藏
页码：1527 / 1533
页数：7
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