Effective Iterative Program Synthesis with Knowledge Searched from Internet

Jiaxin Liu, Wei Dong, Binbin Liu, Yating Zhang, Daiyan Wang
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Abstract

This paper presents the ongoing work of studying the iterative program synthesis based on knowledge searched from the Internet, which can fairly reduce the scale of program space and improve the efficiency of synthesis. First, we implement a tool named Args(api Recommendation via General Search) to obtain the API knowledge from the Internet. Second, we propose an iterative method that incrementally constructs the program space to quickly approach the target program. The initial experimental result shows the effectiveness of our work.
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基于网络知识检索的有效迭代程序综合
本文介绍了基于互联网知识搜索的迭代程序综合的研究工作,该方法可以较好地减小程序空间的规模,提高综合效率。首先,我们实现了一个名为Args(api Recommendation via General Search)的工具,从互联网上获取api知识。其次,我们提出了一种迭代方法,增量构建程序空间以快速接近目标程序。初步的实验结果表明了我们工作的有效性。
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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