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Large language models are becoming increasingly practical for translatingcode across programming languages, a process known as $transpiling$. Eventhough automated transpilation significantly boosts developer productivity, akey concern is whether the generated code is correct. Existing work initiallyused manually crafted test suites to test the translations of a small corpus ofprograms; these test suites were later automated. In contrast, we devise thefirst approach for automated, functional, property-based testing of codetranslation models. Our general, user-provided specifications about thetranspiled code capture a range of properties, from purely syntactic to purelysemantic ones. As shown by our experiments, this approach is very effective indetecting property violations in popular code translation models, andtherefore, in evaluating model quality with respect to given properties. Wealso go a step further and explore the usage scenario where a user simply aimsto obtain a correct translation of some code with respect to certain propertieswithout necessarily being concerned about the overall quality of the model. Tothis purpose, we develop the first property-guided search procedure for codetranslation models, where a model is repeatedly queried with slightly differentparameters to produce alternative and potentially more correct translations.Our results show that this search procedure helps to obtain significantlybetter code translations.

Automatically Testing Functional Properties of Code Translation Models