Phrase-Based Statistical Translation of Programming Languages
Phrase-based statistical machine translation approaches have been highly successful in translating between natural languages and are heavily used by commercial systems (e.g. Google Translate).
The main objective of this work is to investigate the applicability of these approaches for translating between programming languages. Towards that, we investigated several variants of the phrase-based translation approach: i) a direct application of the approach to programming languages, ii) a novel modification of the approach to incorporate the grammatical structure of the target programming language (so to avoid generating target programs which do not parse), and iii) combines ii) with custom rules added to improve the quality of the translation.
To experiment with the above systems, we investigated machine translation from C# to Java. For the training, which takes about 60 hours, we used a parallel corpus of 20,499 C#-to-Java method translations. We then evaluated each of the three systems above by translating 1,000 C# methods. Our experimental results indicate that with the most advanced system, about 60% of the translated methods compile (the top ranked) and out of a random sample of 50 correctly compiled methods, 68% (34 methods) were semantically equivalent to the reference solution.
Fri 24 OctDisplayed time zone: Tijuana, Baja California change
10:30 - 12:00 | Session the FourthOnward! Papers at Salon A Chair(s): Emery D. Berger University of Massachusetts, Amherst | ||
10:30 22mTalk | Phrase-Based Statistical Translation of Programming Languages Onward! Papers | ||
10:52 22mTalk | Interleaving of Modification and Use in Data-driven Tool Development Onward! Papers Marcel Taeumel Hasso Plattner Institute, Michael Perscheid Hasso Plattner Institute, Bastian Steinert Hasso Plattner Institute, Jens Lincke Hasso Plattner Institute, Robert Hirschfeld HPI | ||
11:15 22mTalk | Unifying Textual and Visual: a Theoretical Account of the Visual Perception of Programming Languages Onward! Papers Stéphane Conversy University of Toulouse - ENAC | ||
11:37 22mTalk | Variational Data Structures: Exploring Tradeoffs in Computing with Variability Onward! Papers Eric Walkingshaw University of Marburg, Christian Kästner Carnegie Mellon University, Martin Erwig Oregon State University, Sven Apel University of Passau, Eric Bodden Fraunhofer SIT and TU Darmstadt |