数据库逻辑错误检测系统DLBD的演示

IF 2.6 3区计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS

Proceedings of the Vldb Endowment Pub Date : 2023-08-01 DOI:10.14778/3611540.3611584

Xiu Tang, Sai Wu, Dongxiang Zhang, Ziyue Wang, Gongsheng Yuan, Gang Chen

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引用次数: 0

摘要

数据库管理系统(dbms)容易出现逻辑错误，从而导致错误的查询结果。当前的调试工具仅限于单表查询，并且存在缺乏真实结果和重复查询空间探索等问题。在本文中，我们演示了DLBD，一个自动检测数据库中的逻辑错误的系统。DLBD通过提供自动模式和查询生成以及基本事实查询结果检索来提供整体逻辑错误检测。此外，DLBD为每个bug提供最小的测试用例和根本原因分析，以帮助开发人员重现和修复检测到的bug。DLBD结合启发式和领域特定知识来有效地修剪搜索空间，并采用查询空间探索机制来避免重复搜索。最后，DLBD利用分布式处理框架以可扩展和有效的方式测试数据库逻辑错误。我们的系统为开发人员提供了一种可靠而有效的方法来检测和修复dbms中的逻辑错误。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A Demonstration of DLBD: Database Logic Bug Detection System

Database management systems (DBMSs) are prone to logic bugs that can result in incorrect query results. Current debugging tools are limited to single table queries and struggle with issues like lack of ground-truth results and repetitive query space exploration. In this paper, we demonstrate DLBD, a system that automatically detects logic bugs in databases. DLBD offers holistic logic bug detection by providing automatic schema and query generation and ground-truth query result retrieval. Additionally, DLBD provides minimal test cases and root cause analysis for each bug to aid developers in reproducing and fixing detected bugs. DLBD incorporates heuristics and domain-specific knowledge to efficiently prune the search space and employs query space exploration mechanisms to avoid the repetitive search. Finally, DLBD utilizes a distributed processing framework to test database logic bugs in a scalable and efficient manner. Our system offers developers a reliable and effective way to detect and fix logic bugs in DBMSs.

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来源期刊

Proceedings of the Vldb Endowment Computer Science-General Computer Science

CiteScore

7.70

自引率

0.00%

发文量

期刊介绍： The Proceedings of the VLDB (PVLDB) welcomes original research papers on a broad range of research topics related to all aspects of data management, where systems issues play a significant role, such as data management system technology and information management infrastructures, including their very large scale of experimentation, novel architectures, and demanding applications as well as their underpinning theory. The scope of a submission for PVLDB is also described by the subject areas given below. Moreover, the scope of PVLDB is restricted to scientific areas that are covered by the combined expertise on the submission’s topic of the journal’s editorial board. Finally, the submission’s contributions should build on work already published in data management outlets, e.g., PVLDB, VLDBJ, ACM SIGMOD, IEEE ICDE, EDBT, ACM TODS, IEEE TKDE, and go beyond a syntactic citation.