TY - GEN
T1 - Discovering dynamic developer relationships from software version histories by time series segmentation
AU - Siy, Harvey
AU - Chundi, Parvathi
AU - Rosenkrantz, Daniel J.
AU - Subramaniam, Mahadevan
PY - 2007
Y1 - 2007
N2 - Time series analysis is a pmmising appmach to discover temporal patterns from time stamped, numeric data. A novel approach to apply time series analysis to discern temporal information from software version repositories is proposed. Version logs containing numeric as well as non-numeric data are represented as an item-set time series. A dynamic programming based algorithm to optimally segment an item-set time series is presented. The algorithm automatically produces a compacted item-set time series that can be analyzed to discern temporal patterns. The effectiveness of the approach is illustrated by applying to the Mozilla data set to study the change frequency and developer activity profiles. The experimental results show that the segmentation algorithm produces segments that capture meaningful information and is superior to the information content obtaining by arbitrarily segmenting time period into regular time intervals.
AB - Time series analysis is a pmmising appmach to discover temporal patterns from time stamped, numeric data. A novel approach to apply time series analysis to discern temporal information from software version repositories is proposed. Version logs containing numeric as well as non-numeric data are represented as an item-set time series. A dynamic programming based algorithm to optimally segment an item-set time series is presented. The algorithm automatically produces a compacted item-set time series that can be analyzed to discern temporal patterns. The effectiveness of the approach is illustrated by applying to the Mozilla data set to study the change frequency and developer activity profiles. The experimental results show that the segmentation algorithm produces segments that capture meaningful information and is superior to the information content obtaining by arbitrarily segmenting time period into regular time intervals.
UR - http://www.scopus.com/inward/record.url?scp=47349086101&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=47349086101&partnerID=8YFLogxK
U2 - 10.1109/ICSM.2007.4362654
DO - 10.1109/ICSM.2007.4362654
M3 - Conference contribution
AN - SCOPUS:47349086101
SN - 1424412560
SN - 9781424412563
T3 - IEEE International Conference on Software Maintenance, ICSM
SP - 415
EP - 424
BT - ICSM 2007 - Proceedings of the 2007 IEEE International Conference on Software Maintenance
T2 - 23rd International Conference on Software Maintenance, ICSM
Y2 - 2 October 2007 through 5 October 2007
ER -