Database Slicing on Relational Databases

Dávid Tengeri, F. Havasi
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Abstract

Many software systems today use databases to permanently store their data. Testing, bug finding and migration are complex problems in the case of databases that contain many records. Here, our method can speed up these processes if we can select a smaller piece of the database (called a slice) that contains all of the records belonging to the slicing criterion. The slicing criterion might be, for example, a record which gives rise to a bug in the program. Database slicing seeks to select all the records belonging to a specific slicing criterion. Here, we introduce the concept of database slicing and describe the algorithms and data structures necessary for slicing a given database. We define the Table-based and the Record-based slicing algorithms and we empirically evaluate these methods in two scenarios by applying the slicing to the database of a real-life application and to random generated database content.
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关系数据库上的数据库切片
如今,许多软件系统都使用数据库来永久存储数据。在包含许多记录的数据库中,测试、查找错误和迁移是复杂的问题。在这里,如果我们可以选择包含属于切片标准的所有记录的较小的数据库片段(称为切片),我们的方法可以加快这些过程。切片标准可能是,例如,在程序中产生错误的记录。数据库切片寻求选择属于特定切片标准的所有记录。在这里,我们介绍了数据库切片的概念,并描述了对给定数据库进行切片所需的算法和数据结构。我们定义了基于表和基于记录的切片算法,并通过将切片应用于实际应用程序的数据库和随机生成的数据库内容,在两种情况下对这些方法进行了经验评估。
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