当前位置: X-MOL 学术J. Syst. Softw. › 论文详情
Enhancing Example-Based Code Search with Functional Semantics
Journal of Systems and Software ( IF 2.559 ) Pub Date : 2020-03-02 , DOI: 10.1016/j.jss.2020.110568
Zhengzhao Chen; Renhe Jiang; Zejun Zhang; Yu Pei; Minxue Pan; Tian Zhang; Xuandong Li

As the quality and quantity of open source code increase, effective and efficient search for code implementing certain semantics, or semantics-based code search, has become an emerging need for software developers to retrieve and reuse existing source code. Previous techniques in semantics-based code search encode the semantics of loop-free Java code snippets as constraints and utilize an SMT solver to find encoded snippets that match an input/output (IO) query. We present in this article the Quebio approach to semantics-based search for Java methods. Quebio advances the state-of-the-art by supporting important language features like invocation to library APIs and enabling the search to handle more data types like array/List, Set, and Map. Compared with existing approaches, Quebio also integrates a customized keyword-based search that uses as the input a textual, behavioral summary of the desired methods to quickly prune the methods to be checked against the IO examples. To evaluate the effectiveness and efficiency of Quebio, we constructed a repository of 14,792 methods from 723 open source Java projects hosted on GitHub and applied the approach to resolve 47 queries extracted from StackOverflow. Quebio was able to find methods correctly implementing the specified IO behaviors for 43 of the queries, significantly outperforming the existing semantics-based code search techniques. The average search time with Quebio was about 213 seconds for each query.
更新日期:2020-03-07

 

全部期刊列表>>
智控未来
聚焦商业经济政治法律
跟Nature、Science文章学绘图
控制与机器人
招募海内外科研人才,上自然官网
隐藏1h前已浏览文章
课题组网站
新版X-MOL期刊搜索和高级搜索功能介绍
ACS材料视界
x-mol收录
湖南大学化学化工学院刘松
上海有机所
李旸
南方科技大学
西湖大学
伊利诺伊大学香槟分校
徐明华
中山大学化学工程与技术学院
试剂库存
天合科研
down
wechat
bug