RPT：从大代码中有效检索程序翻译
RPT: Effective and Efficient Retrieval of Program Translations from Big Code
摘要：
程序翻译是软件工程中日益增长的需求。手动程序翻译需要源语言和目标语言的编程专业知识。自动化这一过程的一种方法是利用程序的大数据，即，大代码。特别是，可以在Big Code中搜索程序翻译。然而，现有的代码检索技术不是为跨语言代码检索而设计的。其他数据驱动的方法需要人工构建跨语言并行数据集来训练翻译模型。在本文中，我们提出了RPT，一个新的代码翻译检索系统。我们提出了一个轻量级的，但翔实的程序表示，它可以推广到所有的命令PL。此外，我们提出了我们的索引结构和分层过滤机制，从大代码数据库中进行有效的代码检索。
英文摘要：
Program translation is a growing demand in software engineering. Manual program translation requires programming expertise in source and target language. One way to automate this process is to make use of the big data of programs, i.e., Big Code. In particular, one can search for program translations in Big Code. However, existing code retrieval techniques are not designed for cross-language code retrieval. Other data-driven approaches require human efforts in constructing cross-language parallel datasets to train translation models. In this paper, we present RPT, a novel code translation retrieval system. We propose a lightweight but informative program representation, which can be generalized to all imperative PLs. Furthermore, we present our index structure and hierarchical filtering mechanism for efficient code retrieval from a Big Code database.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
