基于上下文的智能化代码复用推荐

彭鑫; 陈驰; 林云

doi:10.11959/j.issn.2096-0271.2021003

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基于上下文的智能化代码复用推荐

专题：数据驱动的软件智能化开发 | 更新时间：2024-06-03

- 基于上下文的智能化代码复用推荐
- Context-based intelligent recommendation for code reuse
- 大数据 2021年7卷第1期页码：2021003-1
- 作者机构：
  
  1. 复旦大学计算机科学技术学院，上海 200438
  2. 上海市数据科学重点实验室，上海 200438
  3. 新加坡国立大学计算机学院，新加坡 117418
- 作者简介：
  
  [ "（1979- ），男，博士，复旦大学教授、计算机科学技术学院副院长、软件学院副院长。中国计算机学会软件工程专业委员会副主任，Journal of Software: Evolution and Process联合主编，ACM Transactions on Software Engineering and Methodology编委，《软件学报》编委，Empirical Software Engineering编委，IEEE软件维护与进化国际会议（ICSME）执行委员（2017—2020年）。2016年获得NASAC青年软件创新奖。主要研究方向为软件开发大数据分析、智能化软件开发、云原生与智能化运维、泛在计算软件系统等" ]
  [ "陈驰（1993- ），男，复旦大学计算机科学技术学院博士生，主要研究方向为智能化软件开发" ]
  [ "林云（1988- ），男，博士，新加坡国立大学计算机学院高级博士后研究员，主要研究方向为软件调试技术、软件测试、代码推荐与代码重构" ]
- 基金信息：
  
  国家重点研发计划基金资助项目;The National Key Research and Development Program of China(2016YFB1000800)
- DOI：10.11959/j.issn.2096-0271.2021003
  中图分类号： TP311
- 网络首发：2021-01，
  
  纸质出版：2021-01-15
- 稿件说明：
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彭鑫, 陈驰, 林云. 基于上下文的智能化代码复用推荐[J]. 大数据, 2021,7(1):2021003-1.

Xin PENG, Chi CHEN, Yun LIN. Context-based intelligent recommendation for code reuse[J]. Big Data Research, 2021, 7(1): 2021003-1.
彭鑫, 陈驰, 林云. 基于上下文的智能化代码复用推荐[J]. 大数据, 2021,7(1):2021003-1. DOI： 10.11959/j.issn.2096-0271.2021003.

Xin PENG, Chi CHEN, Yun LIN. Context-based intelligent recommendation for code reuse[J]. Big Data Research, 2021, 7(1): 2021003-1. DOI： 10.11959/j.issn.2096-0271.2021003.

摘要

基于代码大数据分析、挖掘和学习的智能化代码复用推荐能够有效地提高软件复用的效率和质量，包括特定领域内的共性代码单元以及与领域无关的通用代码单元。围绕基于上下文的智能化代码复用推荐这一主题，阐述了基于模板挖掘的代码复用推荐和基于深度学习的代码复用推荐两个方面的研究工作。在此基础上，针对基于上下文的智能化代码复用推荐的未来发展方向进行了展望。

Abstract

Intelligent code reuse recommendation based on code-related big data analysis

mining

and learning can improve the efficiency and quality of software reuse significantly. The targets of reuse include domain specific common code units and domain independent common code units. Context-based intelligent recommendation for code reuse was focused

template mining based code reuse recommendation and deep learning based code reuse recommendation were described. Based on these two parts of work

the future trend of context based intelligent recommendation for code reuse was discussed further.

关键词

Keywords

references

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