Semantic similarity-based program retrieval: a multi-relational graph perspective

IF 3.4 3区计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS

Frontiers of Computer Science Pub Date : 2023-12-13 DOI:10.1007/s11704-023-2678-8

Qianwen Gou, Yunwei Dong, YuJiao Wu, Qiao Ke

引用次数: 0

Abstract

In this paper, we formulate the program retrieval problem as a graph similarity problem. This is achieved by first explicitly representing queries and program snippets as AMR and CPG, respectively. Then, through intra-level and inter-level attention mechanisms to infer fine-grained correspondence by propagating node correspondence along the graph edge. Moreover, such a design can learn correspondence of nodes at different levels, which were mostly ignored by previous works. Experiments have demonstrated the superiority of USRAE.

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基于语义相似性的程序检索：多关系图的视角

在本文中，我们将程序检索问题表述为图相似性问题。为此，我们首先将查询和程序片段分别明确表示为 AMR 和 CPG。然后，通过层内和层间关注机制，沿着图边传播节点对应关系，从而推断出细粒度的对应关系。此外，这种设计还能学习不同层次节点的对应关系，而这一点在以往的研究中大多被忽略。实验证明了 USRAE 的优越性。

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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来源期刊

Frontiers of Computer Science COMPUTER SCIENCE, INFORMATION SYSTEMS-COMPUTER SCIENCE, SOFTWARE ENGINEERING

CiteScore

8.60

自引率

2.40%

发文量

799

审稿时长

6-12 weeks

期刊介绍： Frontiers of Computer Science aims to provide a forum for the publication of peer-reviewed papers to promote rapid communication and exchange between computer scientists. The journal publishes research papers and review articles in a wide range of topics, including: architecture, software, artificial intelligence, theoretical computer science, networks and communication, information systems, multimedia and graphics, information security, interdisciplinary, etc. The journal especially encourages papers from new emerging and multidisciplinary areas, as well as papers reflecting the international trends of research and development and on special topics reporting progress made by Chinese computer scientists.