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Found 3 papers, 3 papers with code
Exploring and Unleashing the Power of Large Language Models in Automated Code Translation
This paper investigates diverse LLMs and learning-based transpilers for automated code translation tasks, finding that: although certain LLMs have outperformed current transpilers, they still have some accuracy issues, where most of the failures are induced by a lack of comprehension of source programs, missing clear instructions on I/O types in translation, and ignoring discrepancies between source and target programs.
Learning the Relation between Code Features and Code Transforms with Structured Prediction
We instantiate our approach in the context of repair transform prediction for Java programs.
Exhaustive Exploration of the Failure-oblivious Computing Search Space
In this paper, we study, design and perform an experiment that analyzes the size and the diversity of the failure-oblivious behaviors.
Software Engineering
