boyce-codd normal form - Explore the Science & Experts | ideXlab

Scan Science and Technology

Contact Leading Edge Experts & Companies

boyce-codd normal form

The Experts below are selected from a list of 162 Experts worldwide ranked by ideXlab platform

J. Vandenbulcke – 1st expert on this subject based on the ideXlab platform

  • normalization based on fuzzy functional dependency in a fuzzy relational data model
    Information Systems, 1996
    Co-Authors: Guoquing Chen, Etienne E. Kerre, J. Vandenbulcke

    Abstract:

    Abstract In many cases, classical databases need to be extended in order to represent and manipulate uncertain and imprecise information. In a fuzzy relational data model where attribute values are represented by possibility distributions and domains are associated with closeness relations, the problems of update anomalies and data redundancy may still exist. This paper aims to extend the normalization theory of the classical relational data model so as to provide theoretical guidelines for fuzzy relational database design. Based upon the notion of fuzzy functional dependency (FFD), a number of concepts such as relation keys and normal forms are generalized. As a result, q-keys. Fuzzy First normal form (F1NF), q-Fuzzy Second normal form (q-F2NF), q-Fuzzy Third normal form (q-F3NF), and q-Fuzzy boyce-codd normal form (q-FBCNF) have been formulated. Finally, dependency-preserving and lossless-join decompositions into q-F3NFs are discussed.

  • An extended boyce-codd normal form in fuzzy relational databases
    Proceedings of IEEE 5th International Fuzzy Systems, 1996
    Co-Authors: Guoqing Chen, Etienne E. Kerre, J. Vandenbulcke

    Abstract:

    If the relation schemes of any fuzzy database are not properly designed certain anomaly problems may occur when the fuzzy database is updated or maintained. This is because some undesired relationships exist among attributes. Based on the notions of fuzzy functional dependency (FFD) and /spl theta/-keys, the boyce-codd normal form is extended to cope with the anomaly problems caused by partial and transitive FFDs of /spl theta/-prime on some /spl theta/-keys, thus resulting in /spl theta/-fuzzy boyce-codd normal form (/spl theta/-FBCNF). Furthermore, the relationship between /spl theta/-FBCNF and other existing fuzzy normal forms is analyzed, showing that /spl theta/-FBCNF reflects the strongest restriction for attributes. Finally an algorithm is provided that can decompose, in a lossless-join manner, any scheme into a number of /spl theta/-FBCNF schemes.

  • Fuzzy normal forms and a dependency-preserving decomposition into /spl theta/-F3NF
    Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference, 1994
    Co-Authors: Guoqing Chen, Etienne E. Kerre, J. Vandenbulcke

    Abstract:

    In a fuzzy data model where imprecision of both attribute values and relationships among domain elements is taken into account, problems of data redundancy and update anomalies which are similar to those in classical databases are still found to exist. To cope with these problems, a number of fuzzy normal forms have been defined, based on fuzzy functional dependency, to serve as theoretical guidelines for fuzzy relational database design. This results in the notions of /spl theta/-keys, fuzzy first normal form (F1NF), /spl theta/-fuzzy second normal form (/spl theta/-F2NF), /spl theta/-fuzzy third normal form (/spl theta/-F3NF), and /spl theta/-fuzzy boyce-codd normal form (/spl theta/-FBCNF). Furthermore, the scheme decomposition into /spl theta/-F3NF is discussed in the light of the dependency-preserving property.

Csilla Farkas – 2nd expert on this subject based on the ideXlab platform

  • Data Dependencies Preserving Shuffle in Relational Database
    2019 2nd International Conference on Data Intelligence and Security (ICDIS), 2019
    Co-Authors: Hatim Alsuwat, Emad Alsuwat, Tieming Geng, Chin-tser Huang, Csilla Farkas

    Abstract:

    This paper addresses the problem that database shuffling algorithms do not preserve data dependencies. We introduce an approach for preserving functional dependencies and data-driven associations during database shuffle. We use boyce-codd normal form (BCNF) decomposition for preserving functional dependencies. Given a relation R that is not in BCNF form, we recommend to decompose R into BCNF relations R1, …, Rn. Each Ri (i = 1, …,n) is shuffled then rejoined to create the shuffled relation. Our approach guarantees losslessness and preserves functional dependencies. Data-driven associations may also be lost during database shuffling. For this, we generate the transitive closure of attributes that are associated. We require that the associated attributed are shuffled together. We also present our theoretical and empirical results.

  • ICDIS – Data Dependencies Preserving Shuffle in Relational Database
    2019 2nd International Conference on Data Intelligence and Security (ICDIS), 2019
    Co-Authors: Hatim Alsuwat, Emad Alsuwat, Tieming Geng, Chin-tser Huang, Csilla Farkas

    Abstract:

    This paper addresses the problem that database shuffling algorithms do not preserve data dependencies. We introduce an approach for preserving functional dependencies and data-driven associations during database shuffle. We use boyce-codd normal form (BCNF) decomposition for preserving functional dependencies. Given a relation R that is not in BCNF form, we recommend to decompose R into BCNF relations R1, …, Rn. Each Ri (i = 1, …,n) is shuffled then rejoined to create the shuffled relation. Our approach guarantees losslessness and preserves functional dependencies. Data-driven associations may also be lost during database shuffling. For this, we generate the transitive closure of attributes that are associated. We require that the associated attributed are shuffled together. We also present our theoretical and empirical results.

Sebastian Link – 3rd expert on this subject based on the ideXlab platform

  • ADC – normalisation in the presence of lists
    , 2020
    Co-Authors: Sebastian Link, Sven Hartmann

    Abstract:

    In the relational data model (RDM), normal forms are conditions for relation schemata that a database design should satisfy to ensure an absence of processing difficulties with the database. One prime example of such a normal form is the boyce-codd normal form guaranteeing the absence of redundancies and update anomalies caused by functional dependencies (FDs).Many different data models have been introduced over the years trying to capture data beyond relational structures. The success of those advanced data models will depend, in particular, on the study of normal forms. In fact, finding a unifying framework and extending achievements of relational databases to deal with advanced database features such as complex object types are currently two major challenges in database design (Biskup 1995, Biskup 1998).Such a unifying approach, capturing various different data models at a time, can be based on the type systems underlying the various data models. In the present paper, we study normalisation in the presence of base, record and finite list types. Nested lists are used as a data structure whenever order matters. List types are therefore supported by many advanced data models such as genomic sequence, deductive and object-oriented data models including XML.On the basis of a finite axiomatisation of FDs in the presence of lists the Nested List normal form (NLNF) is proposed as a weaker normal form than BCNF. This proposal is semantically justified by formally proving that NLNF is equivalent to the absence of redundancy. Moreover, NLNF is equivalent to the absence of strong insertion and most forms of replacement anomalies, and sufficient for the absence of all types of update anomalies.

  • SQL schema design: foundations, normal forms, and normalization
    Information Systems, 2018
    Co-Authors: Henning Köhler, Sebastian Link

    Abstract:

    Abstract normalization helps us find a database schema at design time that can process the most frequent updates efficiently at run time. Unfortunately, relational normalization only works for idealized database instances in which duplicates and null markers are not present. On one hand, these features occur frequently in real-world data compliant with the industry standard SQL, and especially in modern application domains. On the other hand, the features impose challenges that make it difficult to extend the existing forty year old normalization framework to SQL, and any current extensions are fairly limited. We introduce a new class of functional dependencies and show that they provide the right notion for SQL schema design. Axiomatic and linear-time algorithmic characterizations of the associated implication problem are established. These foundations enable us to propose a Boyce–Codd normal form for SQL. We justify the normal form by showing that it permits precisely those SQL instances which are free from data redundancy. Unlike the relational case, there are SQL schemata that cannot be converted into Boyce–Codd normal form. Nevertheless, for an expressive sub-class of our functional dependencies we establish a normalization algorithm that always produces a schema in Value-Redundancy free normal form. This normal form permits precisely those instances which are free from any redundant data value occurrences other than the null marker. Experiments show that our functional dependencies occur frequently in real-world data and that they are effective in eliminating redundant values from these data sets without loss of information.

  • SIGMOD Conference – SQL Schema Design: Foundations, normal forms, and normalization
    Proceedings of the 2016 International Conference on Management of Data – SIGMOD '16, 2016
    Co-Authors: Henning Köhler, Sebastian Link

    Abstract:

    normalization helps us find a database schema at design time that can process the most frequent updates efficiently at run time. Unfortunately, relational normalization only works for idealized database instances in which duplicates and null markers are not present. On one hand, these features occur frequently in real-world data compliant with the industry standard SQL, and especially in modern application domains. On the other hand, the features impose challenges that have made it impossible so far to extend the existing forty year old normalization framework to SQL. We introduce a new class of functional dependencies and show that they provide the right notion for SQL schema design. Axiomatic and linear-time algorithmic characterizations of the associated implication problem are established. These foundations enable us to propose a boyce-codd normal form for SQL. Indeed, we justify the normal form by showing that it permits precisely those SQL instances which are free from data redundancy. Unlike the relational case, there are SQL schemata that cannot be converted into boyce-codd normal form. Nevertheless, for an expressive sub-class of our functional dependencies we establish a normalization algorithm that always produces a schema in Value-Redundancy free normal form. This normal form permits precisely those instances which are free from any redundant data value occurrences other than the null marker. Experiments show that our functional dependencies occur frequently in real-world data and that they are effective in eliminating redundant values from these data sets without loss of information.