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• W2020161882 abstract "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." @default.
• W2020161882 created "2016-06-24" @default.
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• W2020161882 date "2013-09-01" @default.
• W2020161882 modified "2023-10-16" @default.
• W2020161882 title "ForkSim: Generating software forks for evaluating cross-project similarity analysis tools" @default.
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• W2020161882 doi "https://doi.org/10.1109/scam.2013.6648182" @default.
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