Near-miss function clones in open source software: an empirical study
Journal of Software Maintenance and Evolution: Research and Practice - Working Conference on Reverse Engineering (WCRE 2008)
Are scripting languages really different?
Proceedings of the 4th International Workshop on Software Clones
Automated type-3 clone oracle using Levenshtein metric
Proceedings of the 5th International Workshop on Software Clones
An empirical study on inconsistent changes to code clones at the release level
Science of Computer Programming
Comparative stability of cloned and non-cloned code: an empirical study
Proceedings of the 27th Annual ACM Symposium on Applied Computing
IDE-based real-time focused search for near-miss clones
Proceedings of the 27th Annual ACM Symposium on Applied Computing
An empirical study on clone stability
ACM SIGAPP Applied Computing Review
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
Evaluating the conventional wisdom in clone removal: a genealogy-based empirical study
Proceedings of the 28th Annual ACM Symposium on Applied Computing
Using mutation analysis for a model-clone detector comparison framework
Proceedings of the 2013 International Conference on Software Engineering
On the relationships between domain-based coupling and code clones: an exploratory study
Proceedings of the 2013 International Conference on Software Engineering
Understanding the evolution of type-3 clones: an exploratory study
Proceedings of the 10th Working Conference on Mining Software Repositories
Submodel pattern extraction for simulink models
Proceedings of the 17th International Software Product Line Conference
Tuning research tools for scalability and performance: The NiCad experience
Science of Computer Programming
Genealogical insights into the facts and fictions of clone removal
ACM SIGAPP Applied Computing Review
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In recent years many methods and tools for software clone detection have been proposed. While some work has been done on assessing and comparing performance of these tools, very little empirical evaluation has been done. In particular, accuracy measures such as precision and recall have only been roughly estimated, due both to problems in creating a validated clone benchmark against which toolscan be compared, and to the manual effort required to hand check large numbers of candidate clones. In this paper we propose an automated method for empirically evaluating clone detection tools that leverages mutation-based techniques to overcome these limitations by automatically synthesizing large numbers of known clones based on an editing theory of clone creation. Our framework is effective in measuring recall and precision of clone detection tools for various types of fine-grained clones in real systems without manual intervention.