Search

Data bases play an important role in applied Mathematics. Normalization for relational databases is very important to avoid anomalies of relations which may not be in normalized forms of the third normal forms. But, normalization may be a difficult task, since the designers of the databases may not fully understand the domain of each attribute that are contained in the relation schema or they may not have full understanding about the concept of normalization. In this paper an efficient method that checks the possibility of the need of further normalization using stored data in relations is presented based on possible functional dependencies between attributes in the relations. By checking possible functional dependencies, the database designers can determine the need of further normalization, and may improve the structure of the relation schemas. Experiments were performed for an example of relational database that can be found in the organization of tutorial of MySQL which is a representational database management system, and the experiments showed good results.

We establish a principled schema design framework for data with missing values. The framework is based on the new notion of an embedded functional dependency, which is independent of the interpretation of missing values, able to express completeness and integrity requirements on application data, and capable of capturing redundant data value occurrences that may cause problems with processing data that meets the requirements. We establish axiomatic, algorithmic, and logical foundations for reasoning about embedded functional dependencies. These foundations enable us to introduce generalizations of Boyce-Codd and Third normal forms that avoid processing difficulties of any application data, or minimize these difficulties across dependency-preserving decompositions, respectively. We show how to transform any given schema into application schemata that meet given completeness and integrity requirements, and the conditions of the generalized normal forms. Data over those application schemata are therefore fit for purpose by design. Extensive experiments with benchmark schemata and data illustrate the effectiveness of our framework for the acquisition of the constraints, the schema design process, and the performance of the schema designs in terms of updates and join queries.

This article is about automated algorithm that analyzes the structure of reporting documentation from local educational organizations that provide primary and secondary education. Many types of school’s documentation are not standardized. Because of that, there is a need to develop a solution that could match many kinds of table data from reporting documentation and create an appropriate database structure in third normal form (3NF) with a view to further analysis by local education department’s managers.

Relational database normalization is a formal data organization process that seeks to make the database more flexible by eliminating data redundancy and inconsistencies. Informally, a relational database relationship is often described as "normalized" if it conforms to the third normal form. Most relationships in 3NF are free of insert, update, and delete anomalies. In this work the design of a normalization assistant is presented. The purpose of the presented proposal is to support the teaching and learning process of relational database normalization, making the user take his universal data table to third normal form in an agile and simple way.

We present new algorithms to compute candidate keys and third normal form design of a relational database schema, using strategic port graph rewriting. More precisely, we define port graph rewriting rules and strategies that implement a candidate key definition and Ullman’s algorithm to decompose a relation schema into lossless 3NF schemata. We show the correctness of the resulting database schema by proving soundness, completeness and termination of our strategic graph programs. These rules and strategies provide a declarative and visual description of the algorithms, and permit a fine-grained analysis of the computation steps involved in the normalisation process. The algorithms have been implemented in Porgy, a visual, interactive modelling tool.

The task of designing relational databases has always been the subject of scientific research, as it is associated with a number of interrelated steps. The result of each step is the development of models for presenting the future database with further refinement and, finally, the creation of an adequate relational database as a set of relations with the corresponding links between them. The article focuses on the normalization of databases, as one of the steps to create a datalogical model, namely, the use of the first three Normal Forms. As a result of the analysis carried out in the article, it was concluded that the definition of the Second Normal Form can be modernized and thus achieve two goals: to ensure the correct creation of potential primary keys and, thereafter, the correct external connections between relations, even before creating the data schema in a specific relational database. Moreover, to reconsider the necessity of applying the so-called “strengthened” or a higher version of the Third Normal Form, which speaks of mutual dependencies between key and non-key attributes.

Government WeChat matrix, which has played an important role in the openness of government affairs, public opinion supervision and public services, is one of the main forms of e-government in contemporary China. We took prefecture-level city WeChat public account as the core research object, analyzed the matrix operation mode of government affairs WeChat public account, and proposed a star matrix model. In the meantime, we also designed the corresponding information management system, using first normal form and third normal form mixed database design mode, using dynamic generated static web page as the front-end user interface, to ensure the stability and security of the system, as far as possible to reduce the waiting time for system access, improve the efficiency of implementation. This matrix structure construction and information system implementation method proposed in this paper has certain reference value for the research of related fields.

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.

International audience; Driven by the dominance of the relational model, we investigate how the requirements of applications on the certainty of functional dependencies can improve the outcomes of relational database schema design. For that purpose, we assume that tuples are assigned a degree of possibility with which they occur in a relation, and that functional dependencies are assigned a dual degree of certainty which says to which tuples they apply. A design theory is developed for functional dependencies with degrees of certainty, including efficient axiomatic and algorithmic characterizations of their implication problem. Naturally, the possibility degrees of tuples bring forward different degrees of data redundancy, caused by functional dependencies with the dual degree of certainty. Variants of the classical syntactic Boyce–Codd and Third Normal Forms are established. They are justified semantically in terms of eliminating data redundancy and update anomalies of given degrees, and minimizing data redundancy of given degrees across all dependency-preserving decompositions, respectively. As a practical outcome of our results, designers can simply fix the degree of certainty they target, and then apply classical decomposition and synthesis to the set of functional dependencies whose associated degree of certainty meets the target. Hence, by fixing the certainty degree a designer controls which integrity requirements will be enforced for the application and which data will be processed by the application. The choice of the certainty degree also balances the classical trade-off between query and update efficiency on future database instances. Our experiments confirm the effectiveness of our control parameter, and provide original insight into classical normalization strategies and their implementations.

The purpose of the article is to develop a method for reengineering relational databases, taking into account the presence of implicit interrelated functionally dependent data that affect the structure of the logical model. The following results are obtained: the article proposes an approach to detecting previously unknown functional dependences, based on the analysis of a set of relational database. Classes of relational databases reengineering problems are singled out; the stage of forming the target logical scheme, common to the problems of adaptation and refactoring, is investigated. The sub-task of verification of the relational database logical scheme correspondence to the third normal form within the framework of this stage is considered using the synthesis method; it is shown that its solution involves a number of difficulties, in particular, the need to find the set of functional dependences being performed using the current data instance of some relational database. An approach is proposed for finding a set of functional dependencies from the relational structure data instance. As a direction for further research, one can highlight the implementation of empty values support at the stage of detection of functional dependences, as well as issues of data transfer without loss from the original structure of the database to the target one, obtained as a result of applying the reengineering methods.

In Gunungkidul district, there are many tourist destinations that are worth visiting and have become tourist destinations from various regions outside Gunungkidul district. The context of the problem that underlies this research is the growing interest in developing applications through online map services using Google maps. The purpose of building a google map-based tourist destination information application is to make it easier for tourists to get tourist destination information through an integrated map with the web. The method used to gather needs and analysis is a fact-finding method with conducting unstructured interviews. The author also made direct observations on the spot, this method is very effective for analyzing and discovering system functions and gaining direct knowledge about activities, operations, and processes. The results of this study are database design that has been normalized to the 3rd normal form, and the application of travel information on Google maps. Through functional testing, this application has run well using travel data taken directly in Gunungkidul district.

This paper compares different levels of database normalization process in terms of anomalies removal and storage reduction. Several databases have been normalized up to Third Normal Form (1NF, 2NF and 3NF) in order to investigate the influence of the normalization on the database performance. They are implemented separately with different database systems such as MS Access, SQL Server and Oracle. The percentage of storage reduction and data anomalies are investigated for every normal form and database system. The results show that the data storage is significantly reduced over unnormalized database, approximately between 20 to 30% for 1NF flattening tables and 1NF decomposing table, and between (15% - 22%) and (9% - 22%) for 2NF and 3NF, respectively. The removal of the majority of anomalies is observed in the first normal form while fewer anomalies are removed in the next higher normal forms. For the same database implemented, the comparison between three different database systems shows approximately the same results with slight differences. These differences may be due to the nature, the size of the constraints and metadata on each database system.

The library database design needs to accord certain rules, in relational database, this rule is paradigm. Paradigm is in line with a certain level of relational schema collections. Relational database relationship must meet certain requirements, namely to meet the different paradigms. At present, there are six kinds of relationship database paradigm: the first normal form (1NF), the second normal form (2NF), the third normal form (3NF), BC normal form (BCNF), the fourth normal form (4NF), the fifth normal form (5NF) and the sixth Normal Form (6NF). The 1NF is the minimum paradigm for requirement. Basing on the 1NF, further meeting more requirements is the 2NF and a higher level paradigm, in practical design application, you only need to reach the 3NF.

When an attempt is made to modify tables that have not been sufficiently normalized undesirable sideeffects may follow. This can be further specified as an update, insertion or deletion anomaly depending on whether the action that causes the error is a row update, insertion or deletion respectively. If a relation R has more than one key, each key is referred to as a candidate key of R. Most of the practical recent works on database normalization use a restricted definition of normal forms where only the primary key (an arbitrary chosen key) is taken into account and ignoring the rest of candidate keys. In this paper, we propose an algorithmic approach for database normalization up to third normal form by taking into account all candidate keys, including the primary key. The effectiveness of the proposed approach is evaluated on many real world examples.

Magelang District is implementing the tourism development program that consists of: marketing development, tourism destination development, partnership development, and tourism infrastructure development. Data about tourism in Magelang regency has not been stored correctly according to the rules of database normalization, with redudancy data storage, including the data that stored and informed online. A good information system should be supported by accurate data and stored on a database that has been normalized, so that data can be read by the system or a different program with different goals and views. Based on the analysis of data obtained in Magelang District, there are several the same ways and the same and the different way of storing and displaying information tourism objects. Normalization process conduct on the obtained data until the 3rd normal form to eliminate the partial dependencies and transitive dependencies. The result of the reseach is a database model.

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., Comment: 22 pages and international journal

Introduction Designing database is an art process similar to building a house. Database designers always face the problems of designing a relational database that will be free of database anomalies. These anomalies bring repetition of tuples that delay processing time and occupy memory spaces. Suppose that the value of the attribute BUILDER determines values of the attribute MODEL and PRICE, (BUILDER [right arrow] MODEL, PRICE) and that the value for the attribute MODEL determines the value for PRICE, (MODEL [right arrow] PRICE). Grouping these attributes in relation HOUSE(BUILDER, MODEL, PRICE) has several undesirable properties. First the relationship between MODEL and PRICE is repeated in the relation for each BUILDER who builds a particular MODEL of home. This repetition creates difficulties if a BUILDER who happens to be the last BUILDER of a certain MODEL home is deleted from the relation, then the relationship between the MODEL and its PRICE also disappears from the relation. This is called a deletion anomaly. Similarly, if a new builder who happens to be the first BUILDER of a certain MODEL home is added then the relationship between MODEL of a home and its PRICE will also be added. This is called an insertion anomaly. Suppose that the relationship between a MODEL and its PRICE is changed e.g. the price is increased; then the MODEL and PRICE relationship should be affected for every BUILDER of the MODEL. This is called update anomaly. These anomalies are undesirable since the user is not likely to realize the consequence of the insertion, deletion or updating. The user may inadvertently affect a relationship that was not intended to be modified. Consistency, insertion, deletion and updating are not probe effecting all groupings of attributes. If the relation HOUSE(BUILDER, MODEL, PRICE) is normalized then the consistency and anomaly problems disappear. Normalization is a step by step reversible process of replacing a given collection of relations by successive collection in which the relations have a progressively simpler and more regular structure (Date & Darwen, 2000). The reversibility guarantees that the original collection of relations can be recovered and therefore no information has been lost. Codd proposed three normal forms which he called first normal form (1NF), second normal form (2NF) and third normal form (3NF). A stronger definition of 3NF was proposed by Boyce and Codd and is known as Boyce-Codd Normal Form (BCNF). All these normal forms except 1NF are based on the functional dependencies among the attributes of a relation (Elmasri & Navathe, 1994). First normal form relates to the structure of the relation. It requires that every attribute of a relation be based on a simple domain. The database designers have no problem to know if a relation violates first normal form. They can put the relation into first normal form algorithmically by replacing a non-simple domain by its constituent simple domains. In the second (2NF), third (3NF) and Boyce Codd normal form (BCNF), there is a need for the database designers to know the real meaning and application of database keys such as candidate key, primary key, super key, etc,. Problem Statement Database designers always find it difficult to determine these keys from relational database schemas. It has been difficult to motivate students and database designers to derive primary, candidate, alternative and super keys because they think this area is dry and theoretical. There are many algorithms to determine the database keys but they look abstract for students. Many database researchers indicated that relational database model to derive database keys tends to be complex for the average designers. Failure to determine the database keys at times leads to poor design that can generate database anomalies. The database key algorithms often require extensive relational algebraic backgrounds that database designers lack. …

Normalisation discusses the traditional normalisation approach to database design — if only because its terminology is required knowledge for anyone who uses databases. This decompositional approach typically begins with a set of business documents that present views of the database. These views become potential table schemas. The potential schemas are examined for redundancies, such as transitive, partial, and Boyce-Codd dependencies. The appendix describes algorithms that remove them and yield 3rd normal form schemas.

This chapter covers the process of transforming an ER diagram into a well-designed relational database. For each normal norm, the chapter presents the rules that relations must meet to reach that normal form, and the design problems that may remain. It also covers the process for transforming relations into higher normal forms, including relational algebra operations, where appropriate.

The traditional relational database model may be extended into a fuzzy database model based on the mathematical framework of fuzzy set theory to process imprecise or uncertain information. While designing such a fuzzy relational database model that does not suffer from data redundancy and anomalies, the present authors have defined several fuzzy normal forms in ref [1]. However, as one decomposes an unnormalized relation into a desired normal form, it should also satisfy the essential properties of dependency preservation and lossless join of relation schemes which take a significant role in the design theory of a relational database. We have concentrated on these two important issues in this paper and have designed algorithms that confirm dependency preservation and lossless join decomposition of an unnormalized relation into the fuzzy third normal form or fuzzy Boyce Codd normal form. The algorithms have been tested and validated with examples.

The proliferation of Windows-based programs for PCs, together with the requirement of many business managers for faster responses to their information needs, has led many business end-users to create, maintain, and query their own databases. These individuals use the output of these queries as the basis for operational, tactical, and strategic decisions. To maximize the benefit of end-users' time, querying these databases must be as efficient as possible. Of even greater importance, the effectiveness of managers' decision-making is directly related to the quality of the information extracted. Because end-user querying is error prone, characterizing the sources of query errors and using that knowledge to improve the effectiveness of end-user query development can improve the quality of information available for decision-making. IS professionals typically design databases in third normal form. End-user databases designed with the help of IS professionals are also likely to be in third normal form. Although third normal form is better for data capture, prior research indicates third normal form is not necessarily the most appropriate normal form for querying. This paper reports the results of an in-depth experiment into the effects of normalization level on the efficiency and effectiveness of end-user querying. The results confirm earlier findings that end-users querying first normal form data structures were both more efficient and more effective than those querying third normal form data structures. This research extends prior research by examining the specific areas where first normal end-users outperform third normal form end-users. In particular, the experiment revealed that first normal form end-users made significantly fewer errors in relation to attribute selection, table selection, and row restriction.

This paper discusses normalization of relations when the candidate keys of a relation have missing information represented by nulls. The paper shows that when the missing information is of the type “not applicable” or “does not exist,” problems and confusion can arise in normalizing relations. Candidate keys with missing information commonly are found in relations that represent information on two entities with a one-to-one relationship between them. The current definition of Boyce-Codd Normal Form (BCNF) is ineffective in identifying poor designs in such relations that may have insertion/deletion anomalies. It is shown that the above problem can be corrected by incorporating the concept of entity integrity rule into the definition of BCNF. This paper also shows that incorporating the entity integrity rule into the definition of either a relation or a candidate key does not provide a satisfactory solution to the problem.

A new normal form, namely, object-normal form (ONF), is introduced. It is shown that the existing definitions of the fifth normal form (5NF) are unsatisfactory. The correct definition is given for the first time. The importance of the 5NF is demonstrated. For improving data representation in a database with a 5NF schema, the notion of negating relation is introduced. It serves as a basis for the new normal form, namely, the sixth normal form. Combining requirements of the ONF and other normal forms, new normal forms are defined: the fourth object-normal form, the fifth object-normal form, and the sixth object-normal form. It is shown that the standard order of steps of the normalization procedure should be changed: first, the specific requirements of the fourth normal form should be satisfied, and only then the requirements of the second normal form, and so forth.

As a result of the shortage of professional programmers to extract timely information from databases, end-users are increasingly developing their own database queries. Because end-user querying is error-prone, characterizing the sources of query errors and using that knowledge to improve the effectiveness of end-user query development can improve the quality of information used for decision making. This paper reports the results of an experiment that investigated the effect of normalization level on query errors. The results show that query errors vary with the normalization level of the database structure and confirm previous findings about query errors increasing with task complexity. End-users querying a first normal form data structure make fewer errors than end-users querying an unnormalized data structure or a third normal form data structure. Furthermore, end-users querying a third normal form data structure make fewer errors than end-users querying an unnormalized data structure.

The issue of providing a formal justification for the use of fourth normal form (4NF) in relational database design is investigated. The motivation and formal definitions for three goals of database design are presented. These goals are the elimination of: redundancy, key-based update anomalies and fact-based replacement anomalies. It is then shown that, depending on the type of constraints permitted, either Boyce-Codd normal form (BCNF) or 4NF are the exact conditions needed to ensure most of the design goals. However, it is also shown that the conditions required to ensure the absence of a particular class of key-based update anomaly are new normal forms which have not previously been identified. In particular, for the case where the only constraints are functional dependencies (FDs), it is shown that the required normal form is a new normal form that is stronger than third normal form (3NF) yet weaker than BCNF. Similarly, in the more general case where both FD and multivalued dependencies (MVDs) are present, the required normal form is a new normal form that is weaker than 4NF.

Although there has been a vast amount of research in the area of relational database design, to our knowledge, there has been very little work that considers whether this theory is still valid when relations in the database may be incomplete. When relations are incomplete and thus contain null values the problem of whether satisfaction is additive arises. Additivity is the property of the equivalence of the satisfaction of a set of functional dependencies (FDs) F with the individual satisfaction of each member of F in an incomplete relation. It is well known that in general, satisfaction of FDs is not additive. Previously we have shown that satisfaction is additive if and only if the set of FDs is monodependent. We conclude that monodependence is a fundamental desirable property of a set of FDs when considering incomplete information in relational database design. We show that, when the set of FDs F either satifies the intersection property or the split-freeness property, then the problem of finding an optimum cover of F can be solved in polynomial time in the size of F; in general, this problem is known to be NP-complete. We also show that when F satisfies the split-freeness property then deciding whether there is a superkey of cardinality k or less can be solved in polynomial time in the size of F, since all the keys have the same cardinality. If F only satisfies the intersection property then this problem is NP-complete, as in the general case. Moreover, we show that when F either satisfies the intersection property or the split-freeness property then deciding whether an attribute is prime can be solved in polynomial time in the size of F; in general, this problem is known to be NP-complete. Assume that a relation schema R is an appropriate normal form with respect to a set of FDs F. We show that when F satisfies the intersection property then the notions of second normal form and third normal form are equivalent. We also show that when R is in Boyce-Codd Normal Form (BCNF), then F is monodependent if and only if either there is a unique key for R, or for all keys X for R, the cardinality of X is one less than the number of attributes associated with R. Finally, we tackle a long-standing problem in relational database theory by showing that when a set of FDs F over R satisfies the intersection property, it also satisfies the split-freeness property (i.e., is monodependent), if and only if every lossless join decomposition of R with respect to F is also dependecy preserving. As a corollary of this result we are able to show that when F satisfies the intersection property, it also satisfies the intersection property, it also satisfies the split-freeness property(i.e., is monodependent), if and only if every lossless join decomposition of R, which is in BCNF, is also dependency preserving. Our final result is that when F is monodependent, then there exists a unique optimum lossless join decomposition of R, which is in BCNF, and is also dependency preserving. Furthermore, this ultimate decomposition can be attained in polynomial time in the size of F.

This paper presents a new dynamic dependency and a new normal form. We give the concept of the stability constraint and establish complete axioms for stability constraints. In addition, we propose a stability normal form. A temporal third normal form can be losslessly decomposed into a sequence of stability constraints. Using the decomposition, the storage space can be reduced. The stability constraints allow to fill a suitable value into a null value. Thus, this null value therefore turns into a known value.

Several approaches have been proposed for the generation of application ontologies from relational databases. Most of these approaches, propose a fully automatic process based on unrealistic assumption, where the input database is well designed, up-to the third normal form (3NF). Real-World databases may contain irrelevant, missing or erroneous information to the ontology learning process. Preparing databases before ontology learning is quite rare. We propose in this paper a methodology for Database Preparation (DBP), composed of three sub-processes: the extraction of a Business Database (BDB), the cleaning of the BDB, and the enrichment of the cleaned BDB. A proof-theoretical case study shows that the proposed methodology is feasible and useful.

In this paper, the adequacy of fifth normal form (5NF) in relational database design is investigated. It is shown that 5NF is inadequate because it does not generalise fourth normal form (4NF) and because it is equivalent to the very stringent requirement that every attribute is a key, a requirement that is effectively impossible to satisfy in practical database design. By restricting the join dependencies (JDs) in the set of constraints to those that do not have superfluous components, the definition of 5NF is then changed to a new normal form, called reduced fifth normal form (5NFR), and it is shown that 5NFR generalises 4NF. It is also shown that 5NFR is a strictly weaker condition than projection-join normal form (PJ/NF), the other normal form that has been proposed for JDs.

In this paper, we give a necessary and sufficient condition for a Boyce-Codd Normal Form (BCNF) relation scheme to be in Fourth Normal Form (4NF). We also give a necessary and sufficient condition for a 4NF relation scheme to be in Projection-Join Normal Form (PJNF). From these results, we derive necessary and sufficient conditions for a BCNF relation scheme to be in PJNF. In addition, we give a less stringent condition for a Third Normal Form (3NF) relation scheme to be in BCNF. Finally, we show that our theorems generalize the results by Date and Fagin (1992).

The purpose of good database logical design is to eliminate data redundancy and isertion and deletion anomalies. In order to achieve this objective for temporal databases, the notions of temporal types , which formalize time granularities, and temporal functional dependencies (TFDs) are intrduced. A temporal type is a monotonic mapping from ticks of time (represented by positive integers) to time sets (represented by subsets of reals) and is used to capture various standard and user-defined calendars. A TFD is a proper extension of the traditional functional dependency and takes the form X → μ Y, meaning that there is a unique value for Y during one tick of the temporal type μ for one particular X value. An axiomatization for TFDs is given. Because a finite set TFDs usually implies an infinite number of TFDs, we introduce the notion of and give an axiomatization for a finite closure to effectively capture a finite set of implied TFDs that are essential of the logical design. Temporal normalization procedures with respect to TFDs are given. Specifically, temporal Boyce-Codd normal form (TBCNF) that avoids all data redundancies due to TFDs, and temporal third normal form (T3NF) that allows dependency preservation, are defined. Both normal forms are proper extensions of their traditional counterparts, BCNF and 3NF. Decompositition algorithms are presented that give lossless TBCNF decompositions and lossless, dependency-preserving, T3NF decompositions.

This paper is intended to present an application system which can facilitate users in converting from Excel spreadsheet to database structure by using data normalization technique. It provides users with an automated system that can develop a database in its third normal form (3NF) from an Excel spreadsheet. There are two major problems of Excel spreadsheet that are emphasized in this project which are data redundancy and update anomaly. Prototyping-based methodology is used in order to develop this system. The system just creates the SQL codes for creating the database structure and populating the database; however, how the users make use of it such as interface for database interaction is not covered at this stage of project. Based on its functionalities, accuracy and performance, this system is able to bring more benefit and convenience for its users.

Relational model is the most essential database model for decades and is examined in various ways. A very important concept in the relational modeling is the concept of dependencies. Particularly a set of functional dependencies and its equivalent minimal cover are discussed here for synthesizing third normal form relations. A traditional synthesis algorithm have been used to reduce the set of functional dependencies, F, into an equivalent minimal cover. This cover is then used to develop a relational schema; however, a given set of functional dependencies may have more than one minimal covers. In turn, different minimal covers may give rise to different relational schema. Database designers had already been agreed upon the use of popular inference rules of Armstrong to obtain minimal covers from the set F of functional dependencies. Despite the frequent use of the traditional synthesis algorithm, there is still a lack of formality and simplicity support in that algorithm to produce a minimum cover, especially; the step(s) of the algorithm in which the set of functional dependencies of F are used to make left-irreducible remain informal. In this paper, an extension is proposed to the synthesis algorithm that aids in to produce an optimal minimal cover more systematically from the given set of functional dependencies. The optimal minimal cover obtained by this extension would be appropriate for synthesizing third normal form relational schema from the universal relation scheme.

In this paper we present some characterizations of relation schemes in second normal form (2NF), third normal form (3NF) and Boyce-Codd normal form (BCNF). It is known [6]that the set of minimal keys of a relation scheme is a Sperner system (an antichain) and for an arbitrary Sperner system there exists a relation scheme the set of minimal keys of which is exactly the given Sperner system. We investigate families of 2NF, 3NF and BCNF relation schemes where the sets of minimal keys are given Sperner systems. We give characterizations of these families. The minimal Armstrong relation has been investigated in the literature [3, 7, 11, 15, 18]. This paper gives new bounds on the size of minimal Armstrong relations for relation schemes. We show that given a relation scheme s such that the set of minimal keys is the Sperner system K, the number of antikeys (maximal nonkeys) of K is polynomial in the number of attributes iff so is the size of minimal Armstrong relation of s. We give a new characterization of relations and relation schemes that are uniquely determined by their minimal keys. From this characterization we give a polynomial-time algorithm deciding whether an arbitrary relation is uniquely determined by its set of all minimal keys. We present a new polynomial-time algorithm testing BCNF property of a given relation scheme.

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.

We introduce a new normal form, called essential tuple normal form (ETNF), for relations in a relational database where the constraints are given by functional dependencies and join dependencies. ETNF lies strictly between fourth normal form and fifth normal form (5NF, also known as projection-join normal form). We show that ETNF, although strictly weaker than 5NF, is exactly as effective as 5NF in eliminating redundancy of tuples. Our definition of ETNF is semantic, in that it is defined in terms of tuple redundancy. We give a syntactic characterization of ETNF, which says that a relation schema is in ETNF if and only if it is in Boyce-Codd normal form and some component of every explicitly declared join dependency of the schema is a superkey.

In explaining functional dependency to students, I have noticed in texts a mixture of two types of elements: intensional (or psychological or meaning) and extensional (patterns of repetition in the data). In this chapter I examine whether it is possible to consider functional dependency, in particular, in second and third normal forms, solely on an extensional basis. The Microsoft Access Analyzer utility seems to do so. I illustrate the mix of intensional and extensional elements in textbook definitions of functional dependency. I conclude that although in principle first, second and third normal form can be done solely by extensional means, in practice intensional considerations are indispensable. Finally, I discuss these questions with respect to the "higher order" normal forms, namely Boyce-Codd, fourth, fifth and Domain/Key normal form.