SEAgle: Effortless Software Evolution Analysis

Author

Chaikalis, T. ; Ligu, E. ; Melas, G. ; Chatzigeorgiou, A.

Author_Institution

Dept. of Appl. Inf., Univ. of Macedonia, Thessaloniki, Greece

fYear

2014

fDate

Sept. 29 2014-Oct. 3 2014

Firstpage

581

Lastpage

584

Abstract

The analysis of software evolution by means of mining public repositories has been established as one of the dominant approaches for empirical studies in software engineering. However, even the investigation of the simplest research question demands a mazy process involving installation and configuration of tools, climbing their learning curve and tedious collection of desired information. Acknowledging the need for effortless querying of remote repositories we introduce a Web-based ´one-click approach´ to perform software evolution analysis of Git projects.

Keywords

Internet; data mining; query processing; software engineering; Git projects; SEAgle; Web-based one-click approach; effortless software evolution analysis; learning curve; public repository mining; remote repository query; software engineering; software evolution analysis; Correlation; Data mining; Engines; Java; Measurement; Software; Software engineering; mining software repositories; software engineering platforms; software evolution analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Software Maintenance and Evolution (ICSME), 2014 IEEE International Conference on

Conference_Location

Victoria, BC

ISSN

1063-6773

Type

conf

DOI

10.1109/ICSME.2014.100

Filename

6976144