A CASE tool for conceptual database design

The paper describes a Computer Aided Software Engineering (CASE) tool to support conceptual database modelling. One popular approach for conceptual database modelling is use of the Entity-Relationship (ER) model. The paper proposes the use of an Enhanced Entity-Relationship (EER) model for conceptual database modelling. This Enhanced Entity-Relationship model extends the Entity-Relationship model by incorporating the generalization/specialization, aggregation and categorization abstractions. The CASE tool, which is based on the Enhanced Entity-Relationship model, is known as the Enhanced Entity-Relationship Diagrammer (EERD). In addition, the CASE tool supports direct visual query and update based on the EERM.     

A conceptual database design approach based on rules and heuristics

Conceptual and logical database design are complex tasks for non-expert designers. Currently, the popular data models for conceptual and logical database design are the entity–relationship (ER) and the relational model, respectively. Logical design methodologies for relational databases have relied on mathematically rigorous approaches which are impractical, or textbook approaches which do not provide the rich constructs to capture real applications. Consequently, designers have to use their intuition to develop their own rules and heuristics. There is a need, therefore, to develop practical rules and heuristics that can be used to handle the complexity of design in real applications. This paper proposes a realistic and detailed approach for conceptual design using the ER model for relational databases. The approach is based on four rules that specify the order in which various types of relationships must be modelled, three rules that pertain to detection of derived relationships, and three heuristics based on observation of constructs in real applications. The approach is illustrated by many examples.     

Using a knowledge learning framework to predict errors in database design

Conceptual data modeling is a critical but difficult part of database development. Little research has attempted to find the underlying causes of the cognitive challenges or errors made during this stage. This paper describes a Modeling Expertise Framework (MEF) that uses modeler expertise to predict errors based on the revised Bloom's taxonomy (RBT). The utility of RBT is in providing a classification of cognitive processes that can be applied to knowledge activities such as conceptual modeling. We employ the MEF to map conceptual modeling tasks to different levels of cognitive complexity and classify current modeler expertise levels. An experimental exercise confirms our predictions of errors. Our work provides an understanding into why novices can handle entity classes and identifying binary relationships with some ease, but find other components like ternary relationships difficult. We discuss implications for data modeling training at a novice and intermediate level, which can be extended to other areas of Information Systems education and training.     

An automated entity–relationship clustering algorithm for conceptual database design

Entity–relationship (ER) modeling is a widely accepted technique for conceptual database design. However, the complexities inherent in large ER diagrams have restricted the effectiveness of their use in practice. It is often difficult for end-users, or even for well-trained database engineers and designers, to fully understand and properly manage large ER diagrams. Hence, to improve their understandability and manageability, large ER diagrams need to be decomposed into smaller modules by clustering closely related entities and relationships. Previous researchers have proposed many manual and semi-automatic approaches for such clustering. However, most of them call for intuitive and subjective judgment from “experts” at various stages of their implementation. We present a fully automated algorithm that eliminates the need for subjective human judgment. In addition to improving their understandability and manageability, an automated algorithm facilitates the re-clustering of ER diagrams as they undergo many changes during their design, development, and maintenance phases.     

A comprehensive framework for modeling set-based business rules during conceptual database design

Business rules are the basis of any organization. From an information systems perspective, these business rules function as constraints on a database helping ensure that the structure and content of the real world—sometimes referred to as miniworld—is accurately incorporated into the database. It is important to elicit these rules during the analysis and design stage, since the captured rules are the basis for subsequent development of a business constraints repository. We present a taxonomy for set-based business rules, and describe an overarching framework for modeling rules that constrain the cardinality of sets. The proposed framework results in various types constraints, i.e., attribute, class, participation, projection, co-occurrence, appearance and overlapping, on a semantic model that supports abstractions like classification, generalization/specialization, aggregation and association. We formally define the syntax of our proposed framework in Backus-Naur Form and explicate the semantics using first-order logic. We describe partial ordering in the constraints and define the concept of metaconstraints, which can be used for automatic constraint consistency checking during the design stage itself. We demonstrate the practicality of our approach with a case study and show how our approach to modeling business rules seamlessly integrates into existing database design methodology. Via our proposed framework, we show how explicitly capturing data semantics will help bridge the semantic gap between the real world and its representation in an information system.     

Logical errors in database SQL retrieval queries

SQL is often used to express questions imposed by users. It is well known that this process is not error-free in that it may result in syntactically or semantically incorrect SQL queries. This article is meant to probe deeper into SQL queries that are incorrect, due to delusion errors. A classification of natural language questions will be introduced. The purpose of this classification is two-fold. Firstly, it gives insight into possible errors and enables us to distinguish between types of errors. Secondly, it is a means of determining the influence of measures (for instance, SQL training) that can be taken to reduce the number of aforementioned errors. For discussion, several of these measures will be presented and related to the classification.Abbreviations RA Relational algebra - SQL structured query language     

Constraint-based functional design verification for conceptual design

In the early stages of mechanical product design, designers not only need to determine the physical structure of the design, but also need to verify that the design functions properly with the allowable values or ranges of values of the relevant design attributes. Existing work on design verification is either aimed at specific design problems, which are generally carried out at the downstream design stages, or aimed at deriving design behavior using a behavioral simulation approach. Functional design verification has largely been neglected by the research society. To tackle this problem, we propose a generic constraint-based approach that is based on a comprehensive functional design model. A number of strategies are proposed for the approach, including strategies for design variables reduction, variable dependency graph development, constraint propagation, and dynamic verification of a design over an assigned set of attributes (variables). The approach is implemented as part of a functional modeling design environment. A simple design verification case is presented to illustrate our approach.     

Collaborative optimization with disciplinary conceptual design

For the first time, a multilevel optimization approach with disciplinary conceptual design is demonstrated. Collaborative optimization is used to decompose an example bridge design problem among two groups of designers – a superstructure design group and a deck design group. The disciplinary groups are allowed to search over different design concepts and formulate the design variables and constraints for each. The autonomy of the two groups is managed by a system-level group which insures that overall system objectives are met and coupling is properly accounted for. Even though discrete conceptual design occurs within the disciplinary groups, a continuous gradient-based optimization algorithm is used at the system level. The procedure was started from a nonoptimal concept, and converged to the optimal concept. Received September 9, 1999     

Security design in distributed database systems

This paper deals with data security design in a distributed environment. A goal of the paper is to present a multiphase security design methodology reflecting the current approach to data base design. The aggregated distributed environment is considered, and a multilevel logical security system architecture is examined. For each level the content of the security logical schemata is defined and described. Finally, mapping rules between the logical levels are presented.     

Intelligennt systems approach to conceptual design

In mechanical system design, the Integrated Computer Aided Design (ICAD) technology has evolved into a new generation of design techniques. It also paves the way for implementing Computer Integrated Manufacturing (CIM) systems. However, the key issue to accomplish the objective in ICAD is the conceptual design automation. Conceptual design is a creative activity and an important decision making during overall product design to reduce energy consumption, to increase raw materials utilization, to obtain more profits, to reduce environmental effects of effluents, and to ensure flexibility, operability, controllability, and safety of manufacturing processes. Therefore, the quality of conceptual design determines the final quality of products and profit of plants. In this article, we first introduce the fundamentals and characteristics of conceptual design. Then, a general problem-solving strategy and methodology to implement conceptual design automation are proposed. an Integrated Distributed Intelligent Design Environment (IDIDE) for developing conceptual design expert systems is presented. Fundamental principles, system organization, and implementation techniques are discussed. Finally, an application case for wheel loader design is studied. © 1995 John Wiley & Sons, Inc.     

Information frameworks for conceptual engineering design

An information modeling approach is used to gain an understanding of the information and decision content of conceptual engineering design. Information frameworks are presented that attempt to represent the key decisions made during conceptual design. Elements of the frameworks are derived from results from design theory and methodology and decision theory. Using a number of products, the frameworks are demonstrated in simulated design situations. The models provide an explicit, generic and consistent perspective for identifying the information content of conceptual designs.     

协同概念设计中用户-设计师协同的研究

以用户需求为基本出发点,将用户引入产品概念设计的全流程,讨论计算机支持的协同概念设计之中的用户与设计师的交互流程以及用户知识的表达,从而提升产品概念设计阶段的创新性、亲和性和舒适性。     

Building a database for product design knowledge retrieval—A case study in robotic design database

In product design process, when dealing with technical problems or initiating a new design, R&D personnel would often turn to technical database to seek inspiration. The building of a database with such documents has not been systematically dealt with. In this paper, several issues on how to build up a product design database are investigated: input source, sampling scheme and quality control. A case study of building a database for robotic design is used to demonstrate the concept. It is an archive of more than 1500 relevant technical papers. A total of 16 graduates are employed as operators in the labeling process and subsequently the hypothesis tests are utilized to process the labeling results. To ensure this database quality, the labeling consistency of each operator and the understanding of each category are tested. With the use of statistical methods, this work proposes a feasible and practical way to create such a database for product design.     

易通打字系统数据库设计

为了实现易通码的计算机练习和输入,运用软件工程学原理、数据库理论,使用VB6.0开发平台,结合Access2003技术设计易通打字系统软件的数据库,为易通打字系统软件的实现奠定了基础。     

Discrimination between design errors and user errors by binomial test

In laboratory usability studies, error collecting and analysis are frequently used methods of software evaluation and usually are capable of revealing the most conspicuous design deficiencies, if there are any. In certain cases, however, it is hard if not impossible to distinguish accidental user errors from systematic errors attributable to design failures without a careful statistical hypothesis testing. An appropriate, additional statistical analysis of the distribution of observed errors along the steps of the standard tasks could add further useful information to the obvious results of the study. For this purpose a simple binomial model is proposed, which proved to be applicable in a case study: by the help of this model it was possible to discover some further design failures in addition to the already obvious ones.     

Generic dependencies and database design

The concept of functional dependencies in databases is generalized and called generic dependencies. Just as a Karnaugh map exhibits all the functional dependencies in a relation, an entropy map represents all the generic dependencies. A generalized normal form useful in database design is defined.