Conceptual graph matching: a flexible algorithm and experiments
Journal of Experimental & Theoretical Artificial Intelligence - Special issue: conceptual graphs workshop
The evolution radar: visualizing integrated logical coupling information
Proceedings of the 2006 international workshop on Mining software repositories
Applying the evolution radar to PostgreSQL
Proceedings of the 2006 international workshop on Mining software repositories
Visual Data Mining in Software Archives to Detect How Developers Work Together
MSR '07 Proceedings of the Fourth International Workshop on Mining Software Repositories
Mining Software Repositories with iSPAROL and a Software Evolution Ontology
MSR '07 Proceedings of the Fourth International Workshop on Mining Software Repositories
Proceedings of the twenty-second IEEE/ACM international conference on Automated software engineering
Proceedings of the 2007 OOPSLA workshop on eclipse technology eXchange
ConcernLines: A timeline view of co-occurring concerns
ICSE '09 Proceedings of the 31st International Conference on Software Engineering
An approach to software evolution based on semantic change
FASE'07 Proceedings of the 10th international conference on Fundamental approaches to software engineering
Exploring, exposing, and exploiting emails to include human factors in software engineering
Proceedings of the 33rd International Conference on Software Engineering
A survey of multiple tree visualisation
Information Visualization
Studying software evolution using artefacts' shared information content
Science of Computer Programming
Comparison of multiple weighted hierarchies: visual analytics for microbe community profiling
EuroVis'11 Proceedings of the 13th Eurographics / IEEE - VGTC conference on Visualization
The bug report duplication problem: an exploratory study
Software Quality Control
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Versioning systems such as CVS exhibit a large potential to investigate and understand the evolution of large software systems. Bug Reporting systems such as Bugzilla help to understand which parts of the system are affected by problems. In this article we present a novel visual approach to uncover the relationship between evolving software and the way it is affected by software bugs. By visually putting the two aspects close to each other, we can characterize the evolution of software artifacts. We validate our approach on 3 very large open source software systems.