基于语义网络的海量源码搜索引擎

doi:10.3969/j.issn.1006-2475.2014.07.004

计算机与现代化 ›› 2014, Vol. 0 ›› Issue (7): 19-23.doi: 10.3969/j.issn.1006-2475.2014.07.004

基于语义网络的海量源码搜索引擎

(1.上海交通大学软件学院，上海 200240; 2.江西省计算技术研究所，江西南昌 330003)

收稿日期:2014-04-22 出版日期:2014-07-16 发布日期:2014-07-17
作者简介:胡翔(1988-)，男，浙江宁波人，上海交通大学软件学院硕士研究生，研究方向：机器学习，程序分析与自然语言理解; 舒礼莲(1966-)，女，江西南昌人，江西省计算技术研究所技术员，本科，研究方向：计算机应用。

Search Engine of Massive Source Code Based on Semantic Network

(1. School of Software, Shanghai Jiaotong University, Shanghai 200240, China;
2. Jiangxi Institute of Computing Technology, Nanchang 330003, China)

Received:2014-04-22 Online:2014-07-16 Published:2014-07-17

摘要/Abstract

摘要： 提出一种通过类自然语言输入在海量源码库中进行代码搜索的方法，旨在提高开源代码在方法层面的重用性。相比于传统的关键字匹配的海量源码搜索方案与基于自然语言的上下文相关的项目内定位方法，本文的程序分析结合语义网络的算法既可解决前者由于源码中缩写与近义词问题带来的目标无法匹配的问题，同时也可解决基于自然语言的源码定位受限于指定项目无法在应用于海量源码搜索的限制。最后通过实验验证引擎的可靠性与可用性。

关键词: 大数据挖掘, 代码推荐, 程序分析, 语义网络

Abstract: This paper proposes an analyzing and searching method which is capable of searching massive source codes whose function is close to the natural language input. Compared with traditional massive source code search engine based on keyword matching algorithm and source code location algorithm based on natural language, this approach solved the mismatch problem in keyword matching algorithm caused by abbreviation and similarity word in source code and the limitation to a specified project of later solution by innovative approach. Experiment is practiced to prove the reliability and usability of this engine.

Key words: big data mining, code recommendation, program analysis, semantic network

中图分类号:

TP312

胡翔1，舒礼莲2. 基于语义网络的海量源码搜索引擎[J]. 计算机与现代化, 2014, 0(7): 19-23.

HU Xiang1, SHU Li-lian2 .

Search Engine of Massive Source Code Based on Semantic Network

[J]. Computer and Modernization, 2014, 0(7): 19-23.

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基于语义网络的海量源码搜索引擎

Search Engine of Massive Source Code Based on Semantic Network

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