定位SQL谓词中的错误

Yun Guo, Amihai Motro, Nan Li
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引用次数: 3

摘要

故障定位技术已应用于使用SQL或基于SQL的语言的数据库和以数据为中心的应用程序。但是,现有的技术只能识别有错误的SQL语句,而不能确定错误在SQL语句中的精确位置。由于SQL语句可能相当复杂,因此程序员仍然面临着困难的修复工作。提出了一种基于行动态切片和增量调试的SQL谓词多类型故障定位方法。我们的方法在一个名为ALTAR的工具中实现,并在两个公开可用的数据库上进行了实验。当现有的故障定位技术应用于SQL语句中的“向下钻取”时,我们的方法可以与这些技术进行比较。结果表明,该方法可以发现更多类型的断层。此外,对于现有方法发现的故障类型,ALTAR更为精确。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Localizing Faults in SQL Predicates
Fault localization techniques have been applied to database and data-centric applications that use SQL or SQL-based languages. However, existing techniques can only identify the SQL statements that have faults, but not determine the precise location of the faults within SQL statements. Since SQL statements can be rather complex, programmers are still left with a difficult repair chore. We propose a novel fault localization method to localize multiple types of faults in SQL predicates, that is based on row-based dynamic slicing and delta debugging. Our method was implemented in a tool called ALTAR, and experiments were performed on two publicly available databases. Our method can be compared with existing fault localization techniques when these are applied to "drill-down" in SQL statements. The results showed that ALTAR can discover more types of faults. Moreover, for the type of faults discovered by current methods, ALTAR is more precise.
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