Using multivariate time series and association rules to detect logical change coupling: An empirical study

Authors:
Gerardo Canfora;Michele Ceccarelli;Luigi Cerulo;Massimiliano Di Penta
Affiliations:
Dept. of Engineering-RCOST, University of Sannio, Italy;Dept. of Biological and Environmental Studies, University of Sannio, Italy;Dept. of Biological and Environmental Studies, University of Sannio, Italy;Dept. of Engineering-RCOST, University of Sannio, Italy
Venue:
ICSM '10 Proceedings of the 2010 IEEE International Conference on Software Maintenance
Year:
2010

Citing 0
Cited 4

Nothing else matters: what predictive model should I use?

Proceedings of the 7th International Conference on Predictive Models in Software Engineering
Connectivity of co-changed method groups: a case study on open source systems

CASCON '12 Proceedings of the 2012 Conference of the Center for Advanced Studies on Collaborative Research
The impact of tangled code changes

Proceedings of the 10th Working Conference on Mining Software Repositories
An empirical analysis of the co-evolution of schema and code in database applications

Proceedings of the 2013 9th Joint Meeting on Foundations of Software Engineering

Quantified Score

Hi-index	0.00

Visualization

Abstract

In recent years, techniques based on association rules discovery have been extensively used to determine change-coupling relations between artifacts that often changed together. Although association rules worked well in many cases, they fail to capture logical coupling relations between artifacts modified in subsequent change sets.