Verifying Semistructured Data Normalization Using PVS

The dramatic expansion of semistructured data has led to the development of database systems for manipulating the data. Despite its huge potential, there is still a lack of formality and verification support in the design of good semistructured databases. Like traditional database systems, developed semistructured database systems should contain minimal redundancies and update anomalies, in order to store and manage the data effectively. Several normalization algorithms have been proposed to satisfy these needs, by transforming the schema of the semistructured data into a better form. It is essential to ensure that the normalized schema remains semantically equivalent to its original form. In this paper, we present tool support for reasoning about the correctness of semistructured data normalization. The proposed approach uses the ORA-SS data modeling notation and defines its correctness criteria and rules in the PVS formal language. It further utilizes the PVS theorem prover to perform automated checking on the normalized schema, checking that functional dependencies are preserved, no data is lost and no spurious data is created. In summary, our approach not only investigates the characteristics of semistructured data normalization, but also provides a scalable and automated first step towards reasoning about the correctness of normalization algorithms on semistructured data.