An automatic framework for extracting and classifying near-miss clone genealogies

Saha, Ripon K.; Roy, Chanchal K.; Schneider, Kevin A.

doi:10.1109/icsm.2011.6080796

Cited by 42 publications

(28 citation statements)

References 16 publications

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“…In another study Saha and colleagues [32] evaluated clone genealogies of three open-source projects. They manually analyzed many of the detected genealogies considering predefined change patterns and conclude that their approach is scalable while maintaining high precision and recall.…”

Section: A Clone Evolutionmentioning

confidence: 98%

An Empirical Study of Clone Removals

Bazrafshan

Koschke

2013

2013 IEEE International Conference on Software Maintenance

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It is often claimed that duplicated source code is a threat to the maintainability of a software system and that developers should manage code duplication. A previous study analyzed the evolution of four software systems and found a remarkable discrepancy between code clones detected by a state-of-the-art clone detector and those deliberately removed by developers as the scope of the clones hardly ever matched. However, the results are based on a relatively small amount of data and need to be validated by a more extensive analysis. In this paper, we present an extension of this study by analyzing deliberate as well as accidental removals of code duplication in the evolution of eleven systems. Based on our findings, we could confirm the results of the previous study. Beyond that we found that accidental removals of cloned code occur slightly more often than deliberate removals and that many clone removals were in fact incomplete.

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Section: A Clone Evolutionmentioning

confidence: 98%

An Empirical Study of Clone Removals

Bazrafshan

Koschke

2013

2013 IEEE International Conference on Software Maintenance

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“…For the purpose of clone management, detecting and studying clone genealogies is another important research topic, and there have been a few genealogy detectors (e.g., [13]). The technology used in ForkSim can easily be adapted to generate software versions rather than software variants for evaluating genealogy detectors' performance.…”

Section: Cross-project Similarity Tool Performance Evaluationmentioning

confidence: 99%

ForkSim: Generating software forks for evaluating cross-project similarity analysis tools

Svajlenko

Roy

Duszynski

2013

2013 IEEE 13th International Working Conference on Source Code Analysis and Manipulation (SCAM)

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Software project forking, that is copying an existing project and developing a new independent project from the copy, occurs frequently in software development. Analysing the code similarities between such software projects is useful as developers can use similarity information to merge the forked systems or migrate them towards a reuse approach. Several techniques for detecting cross-project similarities have been proposed. However, no good benchmark to measure their performance is available. We developed ForkSim, a tool for generating datasets of synthetic software forks with known similarities and differences. This allows the performance of cross-project similarity tools to be measured in terms of recall and precision by comparing their output to the known properties of the generated dataset. These datasets can also be used in controlled experiments to evaluate further aspects of the tools, such as usability or visualization concepts. As a demonstration of our tool, we evaluated the performance of the clone detector NiCad for similarity detection across software forks, which showed the high potential of ForkSim

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“…• Based on functions [8]: It separates clone detection from each version, functions are mapped across subsequent versions, then clones are mapped based on the mapped functions. To some extent, it improves the efficiency and accuracy of the mapping, but it is susceptible to similar overloaded/overridden functions for its over-reliance on function information.…”

Section: ：：：mentioning

confidence: 99%