RPT: Effective and Efficient Retrieval of Program Translations from Big Code

Binger Chen, Ziawasch Abedjan
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引用次数: 2

Abstract

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. However, existing code retrieval techniques lack the design to cover 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.
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RPT:从大代码中有效和高效地检索程序翻译
程序翻译在软件工程中是一个日益增长的需求。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。然而,现有的代码检索技术缺乏涵盖跨语言代码检索的设计。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。本文提出了一种新的代码翻译检索系统RPT。我们提出了一种轻量级但信息丰富的程序表示,它可以推广到所有命令式PLs。此外,我们提出了从大代码数据库中高效检索代码的索引结构和分层过滤机制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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