Theorem prover approach to semistructured data design

J. Univers. Comput. Sci., 2009

The rapid growth of the World Wide Web has resulted in a dramatic in- crease in semistructured data usage, creating a growing need for effective and efficient utilization of semistructured data. In order to verify the correctness of semistructured data design, precise descriptions of the schemas and transformations on the schemas must be established. One effective way to achieve this goal is through formal model- ing and automated verification. This paper presents the first step towards this goal. In our approach, we have formally specified the semantics of the ORA-SS (Object- Relationship-Attribute data model for Semistructured data) data modeling language in PVS (Prototype Verification System) and provided automated verification support for both ORA-SS schemas and XML (Extensible Markup Language) data instances using the PVS theorem prover. This approach provides a solid basis for verifying algo- rithms that transform schemas for semistructured data.

Lecture Notes in Computer Science, 2006

Semistructured data is now widely used in both web applications and database systems. Much of the research into this area defines algorithms that transform the data and schema, such as data integration, change management, view definition, and data normalization. While some researchers have defined a formalism for the work they have undertaken, there is no widely accepted formalism that can be used for the comparison of algorithms within these areas. The requirements of a formalism that would be helpful in these situations are that it must capture all the necessary semantics required to model the algorithms, it should not be too complex and it should be easy to use. This paper describes a first step in defining such a formalism. We have modelled the semantics expressed in the ORA-SS (Object Relationship Attribute data model for SemiStructured data) data modelling notation in two formal languages that have automatic verification tools. We compare the two models and present the findings.

Semistructured data is now widely used in both web applications and database systems. There are many research challenges in this area, such as data integra- tion, change management, view definition, and data normalization. Traditionally in these areas a formal- ism is defined for the database model, and properties of the algorithms can be reasoned about, such as the dependency preserving property of the normalization algorithm in the relational data model. Because re- search into semistructured data is still in its infancy, many algorithms have been defined in this area and a number of formalisms have been proposed but there is no widely accepted formalism that is generally ac- cepted to reason about the properties of the algo- rithms. Such a formalism must capture all the nec- essary semantics required to model the algorithms, should not be too complex, and should be easy to use. Another area that has been developing steadily is automatic verification. This involves formally speci-...

13th IEEE International Conference on Engineering of Complex Computer Systems (iceccs 2008), 2008

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.

Electronic Notes in Theoretical Computer Science, 2006

The rapid growth of the World Wide Web has resulted in more data being accessed over the Internet. In turn there is an increase in the use of semistructured data, which plays a crucial role in many web applications particularly with the introduction of XML and its related technologies. This increase in use makes the design of good semistructured data structures essential. The Object Relationship Attribute model for Semistructured data (ORA-SS) is a graphical notation for designing and representing semistructured data. In this paper, we demonstrate an approach to formally validate the ORA-SS data models in order to enhance the correctness of semistructured data design. A mathematical semantics for the ORA-SS notation is defined using the Z formal language, and further validation processes are carried out to check the correctness of the semistructured data models at both the schema and instance levels.

Advances in Web-Age Information Management, 2006

Semistructured data has become prevalent in both web applications and database systems. This rapid growth in use makes the design of good semistructured data essential. Formal semantics and automated reasoning tools enable us to reveal the inconsistencies in a semistructured data model and its instances. The Object Relationship Attribute model for Semistructured data (ORA-SS) is a graphical notation for designing and representing semistructured data. This paper presents a methodology of encoding the semantics of ORA-SS in the Web Ontology Language (OWL) and automatically validating the semistructured data design using the OWL reasoning tool -RACER. Our methodology provides automated consistency checking of an ORA-SS data model at both the schema and instance levels.

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Lecture Notes in Computer Science, 2006

There has been a rapid growth in the use of semistructured data in both web applications and database systems. Consequently, the design of a good semistructured data model is essential. In the relational database community, algorithms have been defined to transform a relational schema from one normal form to a more suitable normal form. These algorithms have been shown to preserve certain semantics during the transformation. The work presented in this paper is the first step towards representing such algorithms for semistructured data, namely formally defining the semantics necessary for achieving this goal. Formal semantics and automated reasoning tools enable us to reveal the inconsistencies in a semistructured data model and its instances. The Object Relationship Attribute model for Semistructured data (ORA-SS) is a graphical notation for designing and representing semistructured data. This paper presents a methodology of encoding the semantics of the ORA-SS notation into the Web Ontology Language (OWL) and automatically verifying the semistructured data design using the OWL reasoning tools. Our methodology provides automated consistency checking of an ORA-SS data model at both the schema and instance levels.

Information & Management, 1990

Mathematical specifications of data models provide formal means to prove the correctness of the models. Such specifications may be used as prototypes to determined the result of transactions on a database. This paper describes the use of logic programming to mechanize the axiomatization of a proposed extension to the relational data model. The extended model is defined using a many-sorted algebra termed DRE-algebra. The DRE-algebra is then directly implemented in PRO-LOG. The implementation helps in verifying the correctness of the DRE-algebra and is used as an early prototype to investigate design decisions.

19th Australian Conference on Software Engineering (aswec 2008), 2008

The rapid increase in semistructured data usage has lead to the development of various database systems for semistructured data. Web services and applications that utilize large amounts of semistructured data require data to remain consistent and be stored efficient. Several normalization algorithms for semistructured database systems have been developed to satisfy these needs. However, these algorithms lack the verification that would ensure that data and constraints among the data are not lost or corrupted during normalization. In this paper, we propose a set of correctness criteria for normalization of semistructured data, which require that functional dependencies are preserved, data is not lost, and spurious data is not created during normalization. We use the Z specification language to provide a precise and declarative definition of our criteria.