Paper Info
Title
A segmentation-based approach for temporal analysis of software version repositories
Abstract
Time series segmentation is a promising approach to discover temporal patterns from time-stamped numeric data. A novel approach to apply time series segmentation to discern temporal information from software version repositories is proposed. Data from such repositories, both numeric and non-numeric, are represented as item-set time series data. A dynamic programming algorithm for optimal segmentation is presented. The algorithm automatically produces a compacted item-set time series that can be analyzed to identify temporal patterns. The effectiveness of the approach is illustrated by analyzing version control repositories of several open-source projects to identify time-varying patterns of developer activity. The experimental results show that the segmentation algorithm produces segments that capture meaningful information and is superior to the information content obtained by arbitrarily segmenting software history into regular time intervals. Copyright © 2008 John Wiley & Sons, Ltd. A preliminary version [1] of this paper appears in the proceedings of the 2007 International Conference On Software Maintenance (ICSM '07), Paris, France.
Year
DOI
Venue
2008
10.1002/smr.v20:3
Journal of Software Maintenance
Keywords
DocType
Volume
version control,time series data,software evolution,time series,version control system,dynamic programming algorithm,information content
Journal
20
Issue
ISSN
Citations 
3
1532-060X
3
PageRank 
References 
Authors
0.49
24
4
Name
Order
Citations
PageRank
Harvey Siy158144.51
Parvathi Chundi214248.59
Daniel J. Rosenkrantz326471114.92
Mahadevan Subramaniam420425.78