Paper Info
Title
Clustering for Monitoring Software Systems Maintainability Evolution
Abstract
This paper presents ongoing work on using data mining clustering to support the evaluation of software systems' maintainability. As input for our analysis we employ software measurement data extracted from Java source code. We propose a two-steps clustering process which facilitates the assessment of a system's maintainability at first, and subsequently an in-cluster analysis in order to study the evolution of each cluster as the system's versions pass by. The process is evaluated on Apache Geronimo, a J2EE 1.4 open source Application Server. The evaluation involves analyzing several versions of this software system in order to assess its evolution and maintainability over time. The paper concludes with directions for future work.
Year
DOI
Venue
2009
10.1016/j.entcs.2009.02.060
Electr. Notes Theor. Comput. Sci.
Keywords
Field
DocType
software system,in-cluster analysis,data mining,apache geronimo,software measurement data,two-steps clustering process,maintainability,ongoing work,evaluation,open source,software,future work,java source code,monitoring software systems maintainability,application server,source code,software measurement,software systems,cluster analysis
Software engineering,Software analytics,Computer science,Software system,Theoretical computer science,Backporting,Software construction,Database,Software measurement,Software development,Software sizing,Maintainability
Journal
Volume
ISSN
Citations 
233,
Electronic Notes in Theoretical Computer Science
6
PageRank 
References 
Authors
0.49
23
7
Name
Order
Citations
PageRank
Panagiotis Antonellis1536.12
D. Antoniou2121.52
Yiannis Kanellopoulos3948.52
Christos Makris426321.94
E. Theodoridis5101.92
Christos Tjortjis617324.40
Nikos Tsirakis7687.11