Automated Metric Visualizations for Analyzing Source Code Repositories

Author

Jaekwon Lee ; Woosung Jung

Author_Institution

Dept. of Comput. Eng., Chungbuk Nat. Univ., Cheongju, South Korea

fYear

2013

fDate

24-26 June 2013

Firstpage

1

Lastpage

2

Abstract

Nowadays, the size of information from software projects are overwhelming developers and maintainers. Thus, researchers have studied to extract useful knowledge from the source code repositories. However, it is difficult to find patterns or trends from the text-style data directly. In this paper, we propose an automated approach to visualize the metrics of multiple projects. The case studies with the Android open source projects from v1.6 to v4.2 show that outliers, patterns or trends of code changes can be effectively detected with our approach.

Keywords

data visualisation; knowledge acquisition; public domain software; software engineering; text analysis; Android open source project; automated metric visualization; code change; information size; pattern finding; software project; source code repository analysis; text-style data; trend finding; useful knowledge extraction; Complexity theory; Data mining; Data visualization; Market research; Measurement; Smart phones; Software;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Science and Applications (ICISA), 2013 International Conference on

Conference_Location

Suwon

Print_ISBN

978-1-4799-0602-4

Type

conf

DOI

10.1109/ICISA.2013.6579464

Filename

6579464