Characterizing and Verifying Queries Via CINSGEN
Characterizing and Verifying Queries Via CINSGEN
复制标题
通过 CINSGEN 表征和验证查询
DOI：
10.1145/3555041.3589721
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发表时间：
2023
期刊：
影响因子：
--
通讯作者：
Yang, Jun
中科院分区：
文献类型：
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作者：
Meng, Hanze;Miao, Zhengjie;Gilad, Amir;Roy, Sudeepa;Yang, Jun
示例数据库实例对于理解复杂查询非常有帮助。不同的示例可以示出其中答案出现在查询结果中并且可以用于测试的替代情况。示例还可以帮助揭示被认为是等效的查询之间的语义差异，例如，当学生试图理解他们的查询与参考解决方案的行为有何不同时，或者当程序员试图查明重写无意中引入的错误以提高可读性或性能时。在本文中，我们建议演示CinsGen，一个系统，可以表征查询，并帮助区分两个查询。给定一个查询，CinsGen生成满足它的最小条件实例（c-instances）。反过来，每个c-instances是多个数据库实例的泛化，产生一个紧凑的表示。因此，使用CinsGen使用户能够获得满足指定查询的所有场景的全面和紧凑的视图，允许查询表征或两个查询之间的区别。
Example database instances can be very helpful in understanding complex queries. Different examples may illustrate alternative situations in which answers emerge in the query results and can be useful for testing. Examples can also help reveal semantic differences between queries that are supposed to be equivalent, e.g., when students try to understand how their queries behave differently from a reference solution, or when programmers try to pinpoint mistakes inadvertently introduced by rewrites meant to improve readability or performance. In this paper, we propose to demonstrate CinsGen, a system that can characterize queries and help distinguish between two queries. Given a query, CinsGen generates minimal conditional instances (c-instances) that satisfy it. In turn, each c-instance is a generalization of multiple database instances, yielding a compact representation. Thus, using CinsGen enables users to obtain a comprehensive and compact view of all scenarios that satisfy a specified query, allowing for query characterization or distinction between two queries.
使用小例子解释错误的查询
DOI：
10.1145/3299869.3319866
发表时间：
2019
期刊：
SIGMOD '19: Proceedings of the 2019 International Conference on Management of Data
影响因子：
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作者：
Miao, Zhengjie;Roy, Sudeepa;Yang, Jun
通讯作者：
Yang, Jun
I-Rex：用于 SQL 的交互式关系查询调试器
DOI：
10.1145/3478432.3499263
发表时间：
2022
期刊：
Proceedings of the 53rd ACM Technical Symposium on Computer Science Education V. 2
影响因子：
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作者：
Yihao Hu;Zhengjie Miao;Zhiming Leong;Haechan Lim;Zachary Zheng;Sudeepa Roy;Kristin Stephens;Jun Yang
通讯作者：
Jun Yang
DOI：
10.1145/3514221.3517898
发表时间：
2022
期刊：
Proceedings of the 2022 International Conference on Management of Data
影响因子：
--
作者：
Gilad, Amir;Miao, Zhengjie;Roy, Sudeepa;Yang, Jun
通讯作者：
Yang, Jun