Visual Analytics in Software Maintenance: A Systematic Literature Review

被引:0
作者
Liu, Kaihua [1 ]
Reddivari, Sandeep [1 ]
机构
[1] Univ North Florida, Jacksonville, FL 32224 USA
来源
PROCEEDINGS OF THE 2023 ACM SOUTHEAST CONFERENCE, ACMSE 2023 | 2023年
关键词
Software Engineering; Software Maintenance; Visual Analytics; COMPREHENSION; VISUALIZATION; SUPPORT; CODE; TOOL; 3D;
D O I
10.1145/3564746.3587022
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The research on visual analytics for software maintenance has noticeabily advanced in the past few years. For many software projects, software maintenance needs an effective and efficient path from data to decision. Visual analytics (VA) creates such a path that enables the user to extract insights by interacting with the relevant information. This paper focuses on VA in software maintenance and has the following goals: investigate the VA adoption and suggest important implications for practice, and identify current research trends, open problems, and areas for improvement. To achieve these goals we conducted a systematic literature review with three research questions and assessed 51 studies published in the past two decades. The results indicate that there is a lack of collaboration between academic researchers and industry practitioners. This impedes the credibility of the proposed tools and methods due to lack of confidence in industry adoption. Furthermore, in this study we identified the need to expand VA support to other programming languages and software maintenance tasks.
引用
收藏
页码:70 / 77
页数:8
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