一句话：提出一种从输入输出示例自动合成文档数据库查询的技术，利用集合抽象剪枝搜索空间。
文档数据库因其灵活复杂的数据模型而广泛应用，但查询编写困难。本文提出一种从输入输出示例自动生成文档数据库查询的合成技术。作者首先设计了一种新的领域特定语言，以代数风格表达一组有代表性的文档数据库查询。在此基础上，合成技术利用一种新颖的集合抽象进行演绎推理，从而高效剪枝搜索空间，快速生成目标查询。评估使用了来自不同来源的110个基准测试，所提技术成功合成108个基准。平均而言，合成器能在数十秒内基于少量输入输出示例生成文档数据库查询，展示了该方法的有效性与效率。
Document databases are increasingly popular in various applications, but their queries are challenging to write due to the flexible and complex data model underlying document databases. This paper presents a synthesis technique that aims to generate document database queries from input-output examples automatically. A new domain-specific language is designed to express a representative set of document database queries in an algebraic style. Furthermore, the synthesis technique leverages a novel abstraction of collections for deduction to efficiently prune the search space and quickly generate the target query. An evaluation of 110 benchmarks from various sources shows that the proposed technique can synthesize 108 benchmarks successfully. On average, the synthesizer can generate document database queries from a small number of input-output examples within tens of seconds.
DOI 原文 ·
@inproceedings{paperbot8894,
title = {Synthesizing Document Database Queries Using Collection Abstractions},
author = {Qikang Liu and Yang He and Yanwen Cai and Byeongguk Kwak and Yuepeng Wang},
booktitle = {ICSE},
year = {2025},
doi = {10.1109/icse55347.2025.00152}
}