期刊文献+
任意字段
题名或关键词
题名
关键词
摘要
作者
第一作者
机构
刊名
分类号
参考文献
作者简介
基金资助
栏目信息
共找到2篇文章
< 1 >
每页显示 20 50 100
已选0条
引用分析
参考文献
引证文献
 统计分析
检索结果
已选文献
显示方式：
An empirical study on cross-phase code modification behaviors in incremental programming projects 认领 引用
1
作者 Jing Jiang Chenhong Ji +1 位作者 Li Zhang Haiyan Yang 《计算机教育》 2026年第6期280-291,共12页
This paper conducts an empirical study on students'code modification behaviors in incremental programming projects by analyzing 40771 code submissions from 371 students through abstract syntax tree(AST)difference ... This paper conducts an empirical study on students'code modification behaviors in incremental programming projects by analyzing 40771 code submissions from 371 students through abstract syntax tree(AST)difference analysis and manual annotation.The study investigates the distribution of code modification types to prior-phase code during iterative development,identifies cross-phase error types,and analyzes refactoring strategies.The findings reveal that error correction and code refactoring constitute the primary types of cross-phase code modifications.Among cross-phase latent errors,special case neglect represents the dominant error type,indicating insufficient coverage of special scenarios in existing test suites.Variable renaming emerges as the most prevalent refactoring behavior,reflecting students'emphasis on code readability.These research findings provide empirical evidence for optimizing incremental curriculum design,improving test cases,and cultivating students'code maintenance capabilities in programming education. 展开更多
关键词 Incremental projects Code modification Error correction Code refactoring Computer science education
暂未订购 下载PDF
Toward an accurate method renaming approach via structural and lexical analyses 认领 引用
2
作者 Junpeng LUO Jingxuan ZHANG +2 位作者 Zhiqiu HUANG Yong XU Chenxing SUN 《Frontiers of Information Technology & Electronic Engineering》 SCIE EI CSCD 2022年第5期732-748,共17页
Methods in programs must be accurately named to facilitate source code analysis and comprehension.With the evolution of software,method names may be inconsistent with their implemented method bodies,leading to inaccur... Methods in programs must be accurately named to facilitate source code analysis and comprehension.With the evolution of software,method names may be inconsistent with their implemented method bodies,leading to inaccurate or buggy method names.Debugging method names remains an important topic in the literature.Although researchers have proposed several approaches to suggest accurate method names once the method bodies have been modified,two main drawbacks remain to be solved:there is no analysis of method name structure,and the programming context information is not captured efficiently.To resolve these drawbacks and suggest more accurate method names,we propose a novel automated approach based on the analysis of the method name structure and lexical analysis with the programming context information.Our approach first leverages deep feature representation to embed method names and method bodies in vectors.Then,it obtains useful verb-tokens from a large method corpus through structural analysis and noun-tokens from method bodies through lexical analysis.Finally,our approach dynamically combines these tokens to form and recommend high-quality and project-specific method names.Experimental results over 2111 Java testing methods show that the proposed approach can achieve a Hit Ratio,or Hit@5,of 33.62%and outperform the state-of-the-art approach by 14.12%in suggesting accurate method names.We also demonstrate the effectiveness of structural and lexical analyses in our approach. 展开更多
关键词 Method renaming Code refactor Deep learning Convolutional neural networks
暂未订购 下载PDF
已选0条
引用分析
参考文献
引证文献
 统计分析
检索结果
已选文献
上一页 1 下一页 到第 页
在线咨询 使用帮助 返回顶部 意见反馈