When you create a relationship from a super type to another entity, if the 'subtree generation' is set to 'table per child' for the source entity, the relation is forward-engineered into an arc. You can declare a super type for an entity (so it appears in a super type's rectangle and as well can or can not inherit its attributes).It may be confusing, because, in the corresponding relational model, an M:N will always be a table with two foreign keys, and if you imagine them like that then an M:N is always identifying for both foreign keys, but, of course, in a relational model, neither 'identifying' nor 'relationship' exist. At the worst, an M:N relationship can be treated as always-identifying. In a ER-model, the term 'Identifying relationship' isn't applicable for M:N relationships.However, anyone decide to use surrogate keys instead, I think. 'Identifying' actually means the foreign key (in the target) is a part of the primary key, so it can't be NULL.However, it may be forward-engineered into some constraints (triggers, for example). Why not? Why can't you forbid a citizen to exist without a passport, for example? But I'm sure it can't be implemented in (forward engineered into) a pure relational model. However, in a ER-model, a source can be optional. I can't understand what the 'source optional' is in a 1:N relationship, in a relational model. In 1:N relationship, the meaning of 'target optional' is that the corresponding attribute can be NULL (for example, a user exists without any subscriptions).This paper identifies how relationship roles specified in the conceptual schema in conj. When the conceptual database schema contains certain classes of cycles, contexts lack the knowledge necessary to automatically generate logical queries from high-level requests. QUICK uses a conceptual knowledge construct called a context to generate corresponding logical-level SQL queries. Also, as the database structure evolves, the high-level queries remain unchanged. decreased because programmers need not be familiar with the structure and format of the underlying logical-level databases to formulate queries. This high-level query interface provides substantial cost savings to the applications development and maintenance process. It allows users and applications to formulate high-level queries to relational databases without specifying information about the underlying logical-level structure. QUICK is a powerful database query tool used to simplify database access. SQL Developer Data Modeler (referred to as Data Modeler) is a data modeling and database design tool that provides an environment for capturing, modeling. Typically such a virtual table is inside a database environment where efficient data retrieval via SQL can be easily achieved while the data set is physically located outside the database environment. Such a dynamic link can be thought of as a logical pointer that allows a virtual table to reference a data set in a storage device outside the database environment. By hosting it means that the data sets are either directly loaded into the database of the warehouse system, or the data sets are accessible by the data warehouse system via a dynamic link. The data warehouse system should be scalable for hosting multiple data sets from various independent sources. There are several specific requirements for the In this chapter we will discuss our project on the development of an integrated scientific data warehouse and data mining environment based on Oracle database technologies. In this research, we use secondary data to test our hypothesis that practical complexity is different from theoretical complexity. Thus, in addition to theoretical complexity, a set of metrics for estimating practical complexity can be developed, based on the most commonly used constructs (instead of all constructs). We hypothesize that UML's complexity is not as daunting as the metrics imply, because not all the constructs are used all the time. On the other hand, the theoretical complexity of the modeling methods does not necessarily relate to the practical complexity. We argue that this set of metrics provides an indication of the theoretical complexity of the modeling methods.

The complexity analysis is formulated based on the number of constructs, associations, roles, and so forth, in a modeling method. A set of complexity indices for UML and the nine diagramming techniques in UML was compiled recently. Unified Modeling Language (UML) is the standard visual modeling language for Object Oriented (OO) systems development, but it has been criticized for its complexity, inconsistent semantics, and ambiguous constructs.

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