Verifying Semistructured Data Normalization Using PVS

Formal Methods in System Design, 2010

The wide adoption of semistructured data has created a growing need for effective ways to ensure the correctness of its organization. One effective way to achieve this goal is through formal specification and automated verification. This paper presents a theorem proving approach towards verifying that a particular design or organization of semistructured data is correct. We formally specify the semantics of the Object Relationship Attribute data model for Semistructured Data (ORA-SS) modeling notation and its correctness criteria for semistructured data normalization using the Prototype Verification System (PVS). The result is that effective verification on semistructured data models and their normalization can be carried out using the PVS theorem prover.

Proceedings of the Second International Conference on Web Information Systems Engineering

Semistructured data has become prevalent with the growth of the Internet. The development of new web applications that require efficient design and maintenance of large amounts of data makes it increasingly important to design "good" semistructured databases to prevent data redundancy and updating anomalies. However, it is not easy, even impossible, for current semistructured data models to capture the semantics traditionally needed for designing databases. In this paper, we show how an Object-Relationship-Attribute model for SemStructured data (ORA-SS) can facilitate the design of "good" semistructured databases. This is accomplished via the normalization of ORA-SS. An XML DTD or Schema generated from a normal form ORA-SS schema diagram has no undesirable redundancy, and thus no updating anomalies for the complying semistructured databases. The general design methodology and detailed steps for converting an ORA-SS schema diagram into a normal form ORA-SS schema diagram are presented. These steps can also be used as guidelines for designing semistructured databases using the ORA-SS model.

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Lecture Notes in Computer Science, 2006

In this paper, basic relational database (DB) normalization algorithms are implemented efficiently as Mathematica modules. It was observed that, Mathematica provided a straightforward platform as opposed to previous ones, mainly Prolog based tools which required complex data structures such as linked list representations with pointers. A Java user interface called JMath-Norm was designed to execute the Mathematica modules in a systematic way. For this purpose, Mathematica's Java link facility (JLink) is utilized to drive the Mathematica kernel. JMath-Norm provides an effective interactive tool in an educational setting for teaching DB normalization theory.

www-vs.informatik.uni-ulm.de

With the present of XML and its use as a database, schema design and normal form theory has attracted novel research interest. In this paper we address the problem of schema design and normalization in XML databases model. We show that, like relational databases, XML documents may contain redundant information, and this redundancy may cause update anomalies. Furthermore, such problems are caused by certain functional dependencies among paths in the document. Based on our research works, in which we defined the functional dependencies and normal forms for XML Schema, we present the decomposition algorithm for converting any XML Schema into normalized one, that satisfies X-BCNF.

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.

PhD Thesis, The University of Hong Kong, 2009

The nature of software applications is evolving very quickly in the past decade since the World Wide Web has been popularized. Some web applications are required to process large datasets which do not have well-defined structures. This has been challenging conventional data engineering methods. A conventional data engineering method typically requires that a system architect should have prior knowledge on what and how data are processed in an application so as to design a good database schema that optimizes data computations and storage. However, for a web application processing large-scale semi-structured and unstructured data, schema design tasks cannot always be handled totally by human, and need to be automated by software tools. In this thesis, I study the problems of schema computations for semi-structured XML data and unstructured RDF data. This thesis consists of two parts. In the first part, I investigate into the XML data interoperability problem of web services. To address this problem, I develop a formal model for XML schemas called Schema Automaton, and derive the computational techniques for schema compatibility testing and subschema extraction. In the second part, I investigate di?erent types of databases for RDF data. For one particular database type called property tables, I propose a new datamining technique namely Attribute Clustering by Table Load to automate the schema design for the database based on the underlying data patterns.

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.

Lecture Notes in Computer Science, 2001

Semi-structured data has become prevalent with the growth of the Internet. The data is usually stored in a traditional database system or in a specialized repository. While many information providers have presented their databases on the web as semi-structured data, other information providers are developing repositories for new application. One such application is e-commerce, which is emerging as a major web-supported application assisting business transactions between multiple parties via the network and involving large amounts of data. Designing a \good" semi-structured database is increasingly crucial to prevent data redundancy, inconsistency and updating anomalies. In this paper, we propose a conceptual approach to design semi-structured databases. A conceptual layer which is based on the popular Entity-Relationship (ER) model is employed to remove anomalies and redundancies at the semantic level. An algorithm to map an ER diagram involving composite attributes weak entity types, recursive, n-ary and ISA relationship sets, and aggregations to a semi-structured schema graph (S3-Graph) used to represent semi-structured data is given. Our study reveals similarities between the S3-Graph and the hierarchical model and nested relations in that all have limitations in modeling situations with nonhierarchical relationships given their tree-like structures.

International Journal of Database Management Systems, 2011

In this paper a tool called RDBNorma is proposed, that uses a novel approach to represent a relational database schema and its functional dependencies in computer memory using only one linked list and used for semi-automating the process of relational database schema normalization up to third normal form. This paper addresses all the issues of representing a relational schema along with its functional dependencies using one linked list along with the algorithms to convert a relation into second and third normal form by using above representation. We have compared performance of RDBNorma with existing tool called Micro using standard relational schemas collected from various resources. It is observed that proposed tool is at least 2.89 times faster than the Micro and requires around half of the space than Micro to represent a relation. Comparison is done by entering all the attributes and functional dependencies holds on a relation in the same order and implementing both the tools in same language and on same machine.

2013

It has been estimated that more than 80 percent of all the computer programming is database related. Studies have shown that the vast majority of the content in the WWW resides in the deep web sources which store their content in backend databases which have been growing by leaps and bounds. Due to its great importance for database applications database schema design has attracted substantial research. Database normalization is a theoretical approach for structuring a database schema and it is very well developed but unfortunately, the theory is not yet understood well by practitioners. It has been difficult to motivate students to learn database normalization because students think the subject to be dry and purely theoretical. In this paper, a tool called Web Based Relational Database Design and Normalization Tool is proposed, which handles normalization for Relational Databases. The tool is suitable for relational data modeling in systems analysis and design and data management pr...

Citeseer

Semi-structured data is becoming increasingly important with the introduction of XML and related languages and technologies. The recent shift from DTDs (document type de nitions) to XML-Schema for XML data highlights the importance of a schema de nition for semi-structured data ...

2000

Abstract. Recently, there have been several proposals of formalisms for modeling semistructured data, which is data that is neither raw, nor strictly typed as in conventional database systems. Semistructured data models are graph-based models, where graphs are used to represent both databases and schemas.

… Information Processing and Management, Vol 29 …, 2004

Normalization is a process of analyzing the given relation schemas based on their Functional dependencies and primary keys to achieve the desirable properties of minimizing redundancy. It aims at creating a set of relational tables with minimum data redundancy that preserve consistency and facilitate correct insertion, deletion, and modification. A normalized database does not show various insertions, deletion and modification anomalies due to future updates. This paper presents a comparison study of manual and automatic normalization technique using sequential as well as parallel algorithm. It is very much time consuming to employ an automated technique to do this data analysis, as opposed to doing it manually. At the same time, the process is tested to be reliable and correct. It produces the dependency matrix and the directed graph matrix, first. It then proceeds with generating the 2NF, 3NF, and BCNF normal forms. All tables are also generated as the procedure proceeds.