1. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 1

2. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Chapter 4 Enhanced Entity-Relationship and UML Modeling

3. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 3 Chapter Outline EER stands for Enhanced ER or Extended ER EER Model Concepts All modeling concepts of basic ER Additional concepts: subclasses/superclasses specialization/generalization Categories attribute inheritance EER is used to model applications more completely and accurately if needed It includes some object-oriented concepts, such as inheritance Fundamental Principles and Processes of Modeling:

4. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 4 Subclasses and Superclasses (1) An entity type may have additional meaningful subgroupings of its entities Example: EMPLOYEE may be further grouped into SECRETARY, ENGINEER, MANAGER, TECHNICIAN, SALARIED_EMPLOYEE, HOURLY_EMPLOYEE,…

5. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 5 Subclasses and Superclasses (2) Each of these subgroupings is a subset of EMPLOYEE entities Each is called a subclass of EMPLOYEE EMPLOYEE is the superclass for each of these subclasses These are called superclass/subclass relationships. Example: EMPLOYEE/SECRETARY, EMPLOYEE/TECHNICIAN

6. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 6 Subclasses and Superclasses (3) These are also called IS-A relationships SECRETARY IS-A EMPLOYEE, TECHNICIAN IS-A EMPLOYEE, …). Note: An entity that is member of a subclass represents the same real-world entity as some member of the superclass The Subclass member is the same entity in a distinct specific role An entity cannot exist in the database merely by being a member of a subclass; it must also be a member of the superclass A member of the superclass can be optionally included as a member of any number of its subclasses

7. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 7 Subclasses and Superclasses (4) Example: A salaried employee who is also an engineer belongs to the two subclasses ENGINEER and SALARIED_EMPLOYEE It is not necessary that every entity in a superclass be a member of some subclass

8. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 8 Attribute Inheritance in Superclass / Subclass Relationships An entity that is member of a subclass inherits all attributes of the entity as a member of the superclass all relationships of the entity as a member of the superclass

9. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 9 Specialization (1) Specialization is the process of defining a set of subclasses of a superclass The set of subclasses is based upon some distinguishing characteristics of the entities in the superclass Example: {SECRETARY, ENGINEER, TECHNICIAN} is a specialization of EMPLOYEE based upon job type. May have several specializations of the same superclass

10. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 10 Specialization (2) Example: Another specialization of EMPLOYEE based on method of pay is {SALARIED_EMPLOYEE, HOURLY_EMPLOYEE}. Superclass/subclass relationships and specialization can be diagrammatically represented in EER diagrams Attributes of a subclass are called specific attributes. For example, TypingSpeed of SECRETARY The subclass can participate in specific relationship types. For example, BELONGS_TO of HOURLY_EMPLOYEE

11. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 11 Example of a Specialization

12. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 12 Generalization The reverse of the specialization process Several classes with common features are generalized into a superclass; original classes become its subclasses Example: CAR, TRUCK generalized into VEHICLE; both CAR, TRUCK become subclasses of the superclass VEHICLE. We can view {CAR, TRUCK} as a specialization of VEHICLE Alternatively, we can view VEHICLE as a generalization of CAR and TRUCK

13. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 13 Generalization and Specialization (1) Diagrammatic notation sometimes used to distinguish between generalization and specialization Arrow pointing to the generalized superclass represents a generalization Arrows pointing to the specialized subclasses represent a specialization We do not use this notation because it is often subjective as to which process is more appropriate for a particular situation We advocate not drawing any arrows in these situations

14. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 14 Generalization and Specialization (2) Data Modeling with Specialization and Generalization A superclass or subclass represents a set of entities Shown in rectangles in EER diagrams (as are entity types) Sometimes, all entity sets are simply called classes, whether they are entity types, superclasses, or subclasses

15. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 15 Constraints on Specialization and Generalization (1) If we can determine exactly those entities that will become members of each subclass by a condition, the subclasses are called predicate- defined (or condition-defined) subclasses Condition is a constraint that determines subclass members Display a predicate-defined subclass by writing the predicate condition next to the line attaching the subclass to its superclass

16. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 16 Constraints on Specialization and Generalization (2) If all subclasses in a specialization have membership condition on same attribute of the superclass, specialization is called an attribute-defined specialization Attribute is called the defining attribute of the specialization Example: JobType is the defining attribute of the specialization {SECRETARY, TECHNICIAN, ENGINEER} of EMPLOYEE If no condition determines membership, the subclass is called user-defined Membership in a subclass is determined by the database users by applying an operation to add an entity to the subclass Membership in the subclass is specified individually for each entity in the superclass by the user

17. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 17 Constraints on Specialization and Generalization (3) Two other conditions apply to a specialization/generalization: Disjointness Constraint: Completeness Constraint:

18. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 18 Constraints on Specialization and Generalization (4) Disjointness Constraint: Specifies that the subclasses of the specialization must be disjointed (An entity can be a member of at most one of the subclasses of the specialization) Specified by d in EER diagram If not disjointed, overlap; that is the same entity may be a member of more than one subclass of the specialization Specified by o in EER diagram

19. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 19 Constraints on Specialization and Generalization (5) Completeness Constraint: Total specifies that every entity in the superclass must be a member of some subclass in the specialization/generalization Shown in EER diagrams by a double line Partial allows an entity not to belong to any of the subclasses Shown in EER diagrams by a single line

20. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 20 Constraints on Specialization and Generalization (6) Hence, we have four types of specialization/generalization: Disjoint, total Disjoint, partial Overlapping, total Overlapping, partial Note: Generalization usually is total because the superclass is derived from the subclasses.

21. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 21 Example of disjoint partial Specialization

22. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 22 Specialization/Generalization Hierarchies, Lattices & Shared Subclasses (1) A subclass may itself have further subclasses specified on it Forms a hierarchy or a lattice Hierarchy has a constraint that every subclass has only one superclass (called single inheritance) In a lattice, a subclass can be subclass of more than one superclass (called multiple inheritance)

23. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 23 Specialization/Generalization Hierarchies, Lattices & Shared Subclasses (2) In a lattice or hierarchy, a subclass inherits attributes not only of its direct superclass, but also of all its predecessor superclasses A subclass with more than one superclass is called a shared subclass Can have specialization hierarchies or lattices, or generalization hierarchies or lattices

24. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 24 Specialization/Generalization Hierarchies, Lattices & Shared Subclasses (3) In specialization, start with an entity type and then define subclasses of the entity type by successive specialization (top down conceptual refinement process) In generalization, start with many entity types and generalize those that have common properties (bottom up conceptual synthesis process) In practice, the combination of two processes is employed

25. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 25 Specialization / Generalization Lattice Example (UNIVERSITY)

26. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 26 Categories (UNION TYPES) (1) All of the superclass/subclass relationships we have seen thus far have a single superclass A shared subclass is subclass in more than one distinct superclass/subclass relationships, where each relationships has a single superclass (multiple inheritance) In some cases, need to model a single superclass/subclass relationship with more than one superclass Superclasses represent different entity types Such a subclass is called a category or UNION TYPE

27. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 27 Categories (UNION TYPES) (2) Example: Database for vehicle registration, vehicle owner can be a person, a bank (holding a lien on a vehicle) or a company. Category (subclass) OWNER is a subset of the union of the three superclasses COMPANY, BANK, and PERSON A category member must exist in at least one of its superclasses Note: The difference from shared subclass, which is subset of the intersection of its superclasses (shared subclass member must exist in all of its superclasses).

28. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 28 Example of categories (UNION TYPES)

29. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 29 Formal Definitions of EER Model (1) Class C: A set of entities; could be entity type, subclass, superclass, category. Subclass S: A class whose entities must always be subset of the entities in another class, is called the superclass C of the superclass/subclass (or IS-A) relationship S/C: S ⊆ C

30. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 30 Formal Definitions of EER Model (2) Specialization Z: Z = {S1, S2,…, Sn} a set of subclasses with same superclass G; hence, G/Si a superclass relationship for i = 1, …., n. G is called a generalization of the subclasses {S1, S2,…, Sn} Z is total if we always have: S1 ∪ S2 ∪ … ∪ Sn = G; Otherwise, Z is partial. Z is disjoint if we always have: Si ∩ S2 empty-set for i ≠ j; Otherwise, Z is overlapping.

31. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 31 Formal Definitions of EER Model (3) Subclass S of C is predicate defined if predicate p on attributes of C is used to specify membership in S; that is, S = C[p], where C[p] is the set of entities in C that satisfy p A subclass not defined by a predicate is called user- defined Attribute-defined specialization: if a predicate A = ci (where A is an attribute of G and ci is a constant value from the domain of A) is used to specify membership in each subclass Si in Z Note: If ci ≠ cj for i ≠ j, and A is single-valued, then the attribute-defined specialization will be disjoint.

32. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 32 Formal Definitions of EER Model (4) Category or UNION type T A class that is a subset of the union of n defining superclasses D1, D2,…Dn, n>1: T ⊆ (D1 ∪ D2 ∪ … ∪ Dn) A predicate pi on the attributes of T. If a predicate pi on the attributes of Di can specify entities of Di that are members of T. If a predicate is specified on every Di: T = (D1[p1] ∪ D2[p2] ∪ … ∪ Dn[pn] Note: The definition of relationship type should have 'entity type' replaced with 'class'.

33. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 33 UML Example for Displaying Specialization / Generalization

34. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 34 Alternative Diagrammatic Notations Symbols for entity type / class, attribute and relationship Displaying attributes Displaying cardinality ratios Various (min, max) notations Notations for displaying specialization / generalization

35. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 35 The Basics Fundamental Principle of Modeling: Data Abstraction Basic Process of Modeling Define building blocks for holding groups of data Use rules of a data model to establish relationships among blocks Add constraints - structural/ semantic

36. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 36 Part 1: Fundamentals of Data Modeling 1 Inputs to Data Modeling 2 The Process of Modeling 3 Data Modeling Abstractions 4 Classification 5 Aggregation 6 Identification 7 Generalization 8 Coverage Constraints in Generalization 9 Cardinality and Participation Constraints

37. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 37 Inputs to Data Modeling Using the products of requirements analysis Verbal and written communication among users and designers Knowledge of meaning of data Existing Programs Existing Files Existing Documents Existing Reports Application Planning / Documentation and Design

38. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 38 Overall Process of Modeling Abstraction Use of some modeling discipline (Data Model) Use of a representation technique Language Diagramming Tools Analysis of business rules/semantic constraints (these are typically beyond the capability of the data model)

39. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 39 Types of Abstractions Classification A is a member of class B Aggregation B,C,D are aggregated into A A is made of/composed of B,C,D Generalization B,C,D can be generalized into A, B is-an A, C is-an A, D is-an A Specialization A can be specialized into B,C,D B,C,D are special cases of A

40. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 40 Classification Abstraction Relationship between a class and its members John Smith, Sheela Patel, and Peter Wang are all employees. They are all members of a class: EMPLOYEE class Each individual employee is a member of the class EMPLOYEE EMPLOYEE John SmithPeter Wang Sheela Patel

41. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 41 Classification Abstraction (contd.) Exhaustive enumeration of members: MONTH JanuaryDecemberFebruary January, February etc. are members of the class “MONTH” Represents “member-of” relationship In object-oriented modeling : MONTH : an Object type or class January … December : objects that belong to class MONTH

42. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 42 Classification - Class Properties Collection of similar entities or concepts into a higher level concept EMPLOYEE class collects all employees into one class A class has properties called “class properties” EMPLOYEE class has class properties - e.g., average salary, total number of employees Each member has values for own properties (e.g. name, address, salary): called member properties

43. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 43 Aggregation Abstraction Defines a new class from a set of classes which are identified as components of the root class CAR Chasis Other Systems Drive-train represents IS-PART-OF (component) relationship Root class: CAR Component Classes: Chassis, Drive-Train, Other Systems, Wheels Root class: Wheels Component Classes: Tires, Tubes, Hub-Caps Wheels Tires Hub-Caps Tubes

44. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 44 Classification and Aggregation Classification and Aggregation are used to build schemas. Example: class Person Representation: Person Name Sex Position RamJohnCarlos MaleFemaleManagerEmployee Name, Sex, and Position aggregate into Person. They are classes themselves. Ram, John, Carlos are classified into Name or Name is a classification of Ram, John, Carlos

45. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 45 Two Contexts for Aggregation Aggregate two or more classes into a higher level concept. It may be considered a relationship or association between them. Context1: CAR is an aggregate (composition) of Chassis, Drive-train, Other Systems, Wheels. Context 2: OWNERSHIP is an aggregate (relationship) of CAR and OWNER OWNERSHIP CAROWNER

46. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 46 Identification Identifies one concept (an instance of it) from another concept. BUILDING ROOM Name Number Identifies

47. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 47 Generalization Abstraction Defines a set-subset relationship between a class and a set of member classes. Establishes a mapping (or a relationship) from the generic class to the member class (or subclass, or subset class). EMPLOYEE StaffManagerEngineer GENERIC CLASS: EMPLOYEE MEMBER CLASS: Engineer, Staff, Manager Implies that all properties associated with the Employee class are inherited by the three leaf classes.

48. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 48 Data Abstraction (contd.) Process of hiding (suppressing) unnecessary details so that the high level concept can be made more visible. This enables programmers, designers, etc., To communicate easily and to understand the application’s data and functional requirements easily. TYPES OF ABSTRACTION Classification:IS-A-MEMBER-OF Aggregation:IS-MADE-OF, IS-ASSOCIATED-WITH Composition:IS-MADE-OF (similar to aggregation) (A COMPRISES B,C,D) Identification:IS-IDENTIFIED-BY Generalization:IS-AIS-LIKEIS-KIND-OF

49. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 49 Coverage Constraints for Generalization Abstraction TYPE 1 : Total vs. Partial coverage Total: The coverage is total if each member of the generic class is mapped to at least one member among the member classes Partial: The coverage is partial if there are some member(s) of the generic class that cannot be mapped to any member among the member classes STUDENT GraduateSpecialUndergraduate (t) total EMPLOYEE HourlySalaried (t) total

50. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 50 Coverage Constraints for Generalization Abstraction (contd.) Partial Coverage Constraint examples: STUDENT Fellowship Student Scholarship Student (p) partial EMPLOYEE ScientistEngineer (p) partial

51. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 51 Coverage Constraints for Generalization Abstraction TYPE 2: EXCLUSIVE VS. OVERLAPPING (Disjointedness Constraint) EXCLUSIVE constraint: A member of the generic class is mapped to one element of at most one subset class. OVERLAPPING constraint: There exists some member of the generic class that can be mapped to two or more of the subset classes. STUDENT ForeignAmerican (t, e) total, exclusive STUDENT Research AssistantGraduate (p, o) partial, overlapping Aid RecipientForeign

52. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 52 Coverage Constraints for Generalization Abstraction (contd.) More examples of different combinations: VEHICLE VanCar (t, o) total, overlapping Two-wheelerThree-wheeler EMPLOYEE Technical Stuff (p, e) partial, exclusive Non-technical StuffManager Truck

53. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 53 Cardinality Constraints Cardinality Constraint: Quantification of the relationship between two concepts or classes (a constraint on aggregation)

54. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 54 Cardinality Constraints (contd.) MINIMUM (A,B) = n At a minimum, one instance of A is related to at least n instances of B. n = 0MIN(A,B) = 0 MIN(Person, Car) = 0 n = 1MIN(A,B) = 1 MIN(Cust, Ship-address) = 1 n =  MIN(A,B) =  NOT POSSIBLE n = a (fixed)MIN(A,B) = a MIN(Car, Wheels) = 4

55. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 55 Cardinality Constraints (contd.) MAXIMUM (A,B) = n At a maximum, one instance of A is related to at least n instances of B. n = 0MAX(A,B) = 0 DOES NOT ARISE n = 1MAX(A,B) = 1 MAX(Cust, Ship-address) = 1 n = inf.MAX(A,B) = inf. MAX(Cust, Orders) = inf. n = a (fixed)MAX(A,B) = a MAX(Stud, Course) = 6

56. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 56 Participation Constraints MIN (A,B) = 0 Optional Participation MIN (A,B) = 1 Mandatory Participation MAX (A,B) = 0 No Participation MIN (A,B) = x, MAX (A,B) = y Range Constrained Participation

57. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 4- 57 Summary of Modeling Concepts ABSTRACTIONS CLASSIFICATION AGGREGATION (COMPOSITION AND ASSOCIATION) IDENTIFICATION GENERALIZATION AND SPECIALIZATION CONSTRAINTS CARDINALITY (Min. and Max) PARTICIPATION COVERAGE (Total vs. Partial, Exclusive vs. Overlapping)

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