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Unveiling the potential of large language models in generating semantic and cross-language clones
Similarly, if someone possesses a code snippet in a particular programming language but seeks equivalent functionality in a different language, a semantic cross-language code clone generation approach could provide valuable assistance. In this study, using SemanticCloneBench as a vehicle, we evaluated how well the GPT-3 model could help generate semantic and cross-language clone variants for a given fragment. We have comprised a diverse set of code fragments and assessed GPT-3s performance in generating code variants. Through extensive experimentation and analysis, where 9 judges spent 158 hours to validate, we investigate the model's ability to produce accurate and semantically correct variants.
Designing for Recommending Intermediate States in A Scientific Workflow Management System
In SciWorCS, we present an interface that users use for selecting the recommendation of intermediate states (i. e., modules' outcomes).
