一句话：通过增广与结构化用户查询，缓解代码搜索中的词汇不匹配问题，支持高效自由形式代码检索。
代码搜索是软件开发中的重要活动，开发者经常查找涉及不同编程概念、API 与平台特性的代码示例。已有 OpenHub、Codota 等互联网规模代码搜索引擎将源代码当作自然语言文档处理，因而性能受限；其核心挑战在于“没有单个词能最好地描述一个编程概念”，即词汇不匹配问题。为提升搜索性能，不仅需要改进搜索空间索引的构建，还需要改进查询映射过程。论文据此提出增广并结构化用户查询，以支持高效的自由形式代码搜索；但所给摘要仅阐述动机与问题，未给出具体方法细节与实验评估结果。
Motivation: Code search is an important activity in software development since developers are regularly searching [6] for code examples dealing with diverse programming concepts, APIs, and specific platform peculiarities. To help developers search for source code, several Internet-scale code search engines, such as OpenHub [5] and Codota [1] have been proposed. Unfortunately, these Internet-scale code search engines have limited performance since they treat source code as natural language documents. To improve the performance of search engines, the construction of the search space index as well as the mapping process of querying must address the challenge that "no single word can be chosen to describe a programming concept in the best way" [2]. This is known in the literature as the vocabulary mismatch problem [3].
DOI 原文 ·
@inproceedings{paperbot4485,
title = {Augmenting and structuring user queries to support efficient free-form code search},
author = {Raphael Sirres and Tegawendé F. Bissyandé and Dongsun Kim and David Lo and Jacques Klein and Kisub Kim and Yves Le Traon},
booktitle = {ICSE},
year = {2018},
doi = {10.1145/3180155.3182513}
}