1. IDEF
Partie 1
IDEF

2. What is IDEF?
Definition: IDEF is the common name referring to classes of enterprise modeling languages.
Objective: IDEF is used for modeling activities necessary to support system analysis, design, improvement or integration.
Originally, IDEF was developed to enhance communication among people trying to understand the system. Now, IDEF is being used for documentation, understanding, design, analysis, planning, and Integration.

3. IDEF History
In the 1970’s, IDEF0 originated in the U.S. Air Force under the Integrated Computer Aided Manufacturing(ICAM) program from a well-established graphical language, the Structured Analysis and Design Technique (SADT).

4. IDEF Family IDEF Family of Methods:
IDEF0: for Function Modeling (purpose:description)
IDEF1: for Information Modeling. (purpose:description)
IDEF1x: for Data Modeling. (purpose:design)
IDEF3: for Process Modeling. (purpose:description)
IDEF4: for Object-Oriented Design. (purpose:design)
IDEF5: for Ontology Description Capture. (purpose:description)

5. IDEF0- Function Modeling Method
IDEF0 models the decisions, actions, and activities of an organization or system, in order to communicate the functional perspective of a system.
IDEF0 models are created as one of the first tasks of a system development effort because they describe:
the functions that are performed,
what is needed to perform those functions,
IDEF0 was released as a standard for Function Modeling by the Computer Systems Laboratory of the National Institute of Standards and Technology. (1993)

6. IDEF0- Function Modeling Method
Syntax:
Context Diagram: is a model of the function at the highest level of inputs, controls, outputs, and mechanisms
Mechanisms
Function Name
Controls
Inputs
Outputs
Inputs: items that trigger the activity
Controls: guide or regulate the activity
Mechanisms: systems, people, equipment used to perform the activity
Outputs: results of performing the activity

7. IDEF0- Function Modeling Method
Decomposition Diagram: links together the context diagrams

8. IDEF1- Information Modeling Method
IDEF1 is a method for both analyzing and communicating the structure and semantics of information within a system.
IDEF1 models are used to:
Identify what information is currently managed in a real-world system, both automated system components, and non-automated objects (e.g. people).
Identify the rules for managing the information.
Identify deficiencies in the current management of the information.
Specify what information will be managed in a TO-BE implementation. (TO-BE implementation: Design of the functional architecture)

9. IDEF1- Information Modeling Method
STRENGTHS
IDEF1 requires active participation of the information users, which serves to accurately model where and how the information is used and managed.
An effective method for documenting the informational requirements of an enterprise, providing a foundation for database design.
IDEF1 enforces a modularity that eliminates the incompleteness, imprecision, inconsistencies, and inaccuracies found in the modeling process.

10. IDEF1x- Data Modeling Method
IDEF1X is a method for designing relational databases.
IDEF1X Model: Graphical and Textual depiction of “What must I know to do what I do?”
IDEF1X is most useful for logical database design after the information requirements are known and the decision to implement a relational database has been made.
IDEF1X was released as a standard for Data Modeling by the Computer Systems Laboratory of the National Institute of Standards and Technology. (1993)

11. IDEF1x- Data Modeling Method
STRENGTHS
Powerful tool for data modeling.
IDEF1X don’t have numerous variants, unlike ER.
Depicts the rules governing the management of information.
Used to validate the concepts in the associated IDEF0 model.
Helps to discover underlying causes for problems.
WEAKNESSES
The modeler must be experienced in order to create good models.
Not suited to serve as an AS-IS analysis tool.

12. IDEF1 (information Model) vs. IDEF1x (Data Model)
focuses on:
Information collected, stored, and managed by the organization
Logical relationships within the organization reflected in the information
Actual data elements in a relational database
Representation & structure of the data
used for:
Problem identification
Requirements definition
Information system design
Logical design of databases & applications
Physical design of database implementation

13. Entity – relation model
IDEF1
Partie 2
Entity – relation model

14. Introduction
Scope
IDEF1 is used to produce a graphical information model which represents the structure and semantics of information within an environment or system.

15. Introduction
Purpose
IDEF1 is used to model data in a standard, consistent, predictable manner in order to manage it as a resource. The primary objectives of this standard are:
To provide a means for completely understanding and analyzing an organization’s data resources;
To provide a common means of representing and communicating the complexity of data;
To provide a method for presenting an overall view of the data required to run an enterprise;
To provide a means for defining an application-independent view of data which can be validated by users and transformed into a physical database design;
To provide a method for deriving an integrated data definition from existing data resources.

16. Introduction Several appellations
Model entity – association
Model entity – relationship
Model object – relationship
First publication by Dr. Pin-Shan (Peter) Chen (陳品山) 1976
Top down approach: from the discourse universe towards the model
The diagrams created using this approach are called ER diagrams.

17. IDEF1- Information Modeling Method
Main IDEF1 Concepts
Entity: The representation of a set of real or abstract things (people, objects, places, events, ideas, combination of things, etc.) that are recognized as the same type because they share the same characteristics and can participate in the same relationships.
Entity Instance: One of a set of real or abstract things represented by an entity. The instance of an entity can be specifically identified by the value of the attribute(s) participating in its primary key.

18. IDEF1- Information Modeling Method
Main IDEF1 Concepts
Attribute: A property or characteristic that is common to some or all of the instances of an entity. An attribute represents the use of a domain in the context of an entity.
Key, Candidate: An attribute, or combination of attributes, of an entity whose values uniquely identify each entity instance.
Key, Composite: A key comprised of two or more attributes.
Attribute, Non-key: An attribute that is not the primary or a part of a composite primary key of an entity. A non-key attribute may be a foreign key or alternate key attribute.

19. IDEF1- Information Modeling Method
Main IDEF1 Concepts
Relationship: An association between two entities or between instances of the same entity.
Relationship Name: A verb or verb phrase which reflects the meaning of the relationship expressed between the two entities shown on the diagram on which the name appears.
Verb Phrase: A phrase used to name a relationship, which consists of a verb and words which comprise the object of the phrase.
Relationship Cardinality: The number of entity instances that can be associated with each other in a relationship.

20. IDEF1- Information Modeling Method
Main IDEF1 Concepts
Constraint, Cardinality: A limit on the number of entity instances that can be associated with each other in a relationship.
Existence Dependency: A constraint between two related entities indicating that no instance of one (child entity) can exist without being related to an instance of the other (parent entity). The following relationship types represent existence dependencies: identifying relationships, categorization relationships and mandatory non-identifying relationships.
Functional Dependency: A special kind of integrity constraint that applies within the confines of a single entity “R”, where each “X” value of “R” has associated with it at most one “Y” value of “R” (at any one time). Attributes “X” and “Y” may be composite.

21. Presentation ATTRIBUTE
Definition : elementary information, nondeductible from another one, presenting an interest in the considered domain.
a value taken by a property is an occurrence
a property is atomic if it can not be decomposed
Synonyms : Attribute, characteristic, constituent,…
Description : a property can be defined by
A name, a label
A type
A length
All properties must be mentioned on a model.
Take care to avoid:
two same names for a property
A same name for two properties
A property must only appear one time in the model

22. Presentation ENTITY, INSTANCE, KEY ENTITIES Definition :
Representation of tangible or intangible elements important for the system to describe
Entity class correspond to a set of entities whose definition is the same
Entity classification inside a class is called classification or instantiation
Entity class can be viewed as a set properties that are gathered
Synonyms : Object
Description :
A name, a label
An identifying characteristic
Some properties
label
List of properties

23. Presentation Student ENTITY, INSTANCE, KEY INSTANCE
Definition : Each property is valuated by an instance which corresponds to a value define in a (finite or infinite) set of values.
Remark : Each occurrence of an entity class have the same properties.
Student
Number
Family name
First name
Ex. Entity class « Student »
All instance have the same properties: number, family name and first name

24. Presentation Student ENTITY, INSTANCE, KEY KEY Definition :
an identifying characteristic is a specific property that allow to identify one and only one entity.
an identifying characteristic is an entity specific property so that there does not exist two occurrences for which this property could take a same value
Example:
Which property can be used as identifying characteristic for a student ?
its student national university subscription number
Formalism : an identifying characteristic is underlined
Student
Number
Family name
First name

25. Presentation RELATIONSHIP, INSTANCE, RELATIONSHIP TYPOLOGY
Definition :
a relationship represents a semantic link between 2 or more entities that belong to the considered universe. A link is mentioned if there is an interest regarding the universe.
a class of associations contents all associations of a same type
a relation must be specific regarding the different entities that are in relation.
a relation can be characterized by specific properties
Synonyms : Association
Description:
A name, a label
Properties, characteristic identifying

26. Presentation RELATIONSHIP, INSTANCE, RELATIONSHIP TYPOLOGY
Formalism :
CALL
NumAnn
Texte
NbLignes
Dom
NbSem
DateRédac
CUSTOMER
NumCli
Nom
Prénom
Rue CP
Ville
JOURNAL
Rub
TarifPrem
Concern
write
Here a customer can write a call which concerns a journal

27. Presentation RELATIONSHIP, INSTANCE, RELATIONSHIP TYPOLOGY INSTANCE
Definition : an association instance represents a specific link between two or more entity occurrence.
Description :
an association instance is made up of one and only one entity instance of each entity that are linked.
all association instance have the same properties 1
DUPONT
René 16
Charente 2
DURAND
Paul
The scheme represents two examples of the association occurrence « live ».

28. Presentation RELATIONSHIP, INSTANCE, RELATIONSHIP TYPOLOGY
RELATION TYPOLOGY
There is no limit regarding the number of entity class that can be in relation.
it is possible to define “bin”ary relation :
It is possible to definite “n”ary relation
CE3
CE4

29. Presentation RELATIONSHIP, INSTANCE, RELATIONSHIP TYPOLOGY
RELATION TYPOLOGY
Reflexive relation
It expresses the links between entity instance
Ex. In project management a task can be previous another one and can be followed by one or more task.
Task
To be previous than N°
of task

30. Presentation Several links can exist between two or more entities
RELATIONSHIP, INSTANCE, RELATIONSHIP TYPOLOGY
RELATION TYPOLOGY
Multiple relation
Several links can exist between two or more entities
EMPLOYEE
Number
Name
live
DEPT
NoDepartment
Name of the department
work

31. Presentation RELATIONSHIP, INSTANCE, RELATIONSHIP TYPOLOGY
RELATION TYPOLOGY
Remark: relationship primary key
1 ) Primary key of a relationship is obtained by associating the primary keys of each entity participating in the relation.
2) Each occurrence of the relationship is concerned by one and only one value of the primary key.

32. Presentation CONSTRAINTS CARDINALITY
Definition : The cardinality of a link between an entity and an association precise the minimum and maximum number of time that an entity instance is concerned by the association
Formalism : Cardinality is noted using two numbers “ m,M ”. “ m ” is the minimal cardinality and “ M ” the maximal cardinality
Minimal cardinality: is the minus number of time for which an entity occurrence can participate to the relation (0 or 1).
Maximal cardinality: is the major number of time for which an entity occurrence can participate to the relation (1 or N).

33. Presentation CONSTRAINTS CARDINALITY
Example : A firm manages products that are stored or not (produced on demand). It has factories that contains at least one product.
A product can not be stored in a factory which means that there can exist one occurrence of a product without any occurrence of storage. 0
A product can be stored, but only in one factory, then one occurrence of product can exist only with one occurrence of storage. 1
A factory stores at the minimum one product. 1
A factory can store more than one product. n
product
store
factory
0,1
1,n
1,n

34. Presentation CONSTRAINTS CARDINALITY
Remark: couple can be (0,1), (0, N), (1, 1) and (1,n)
Remark: a minimal cardinality of 1 is justified by the fact that all occurrence of the entity need that the association exist.
Remark: the discussion around a minimal cardinality 0 or 1 is interesting only if the the maximal cardinality is 1.

35. Presentation Syntactic rules
Entity normalization: all entity that can be replaced by an association must be replaced
Name normalization: the name of an entity, an association or an attribute must be single
Normalization of keys : each entity must have a key (preferably an entirety, incremented automatically)
Normalization of attributes : replace the attributes in several specimens in an additional association of maximum cardinality N and not to add calculable attributes starting from other
Normalization of attributes of associations : attributes of an association must directly depend on the keys of all entities that are associated
Normalization of associations: it is necessary to eliminate phantom associations
Normalization of constraints: the minimal cardinality is always 0 or 1, the maximal cardinality is always 1 or n

36. Normalization
Normal forms

37. Normalization NORMALIZATION RULES
Definition: the process of refining and regrouping attributes in entities according to the normal forms.
Normal Form:
Definition: the condition of an entity relative to satisfaction of a set of normalization theory constraints on its attribution. A specific normal form is achieved by successive reduction of an entity from its existing condition to some more desirable form. The procedure is reversible.
b) Second Normal Form (2NF) - An entity is in 2NF if and only if it is in 1NF and every non-key attribute is fully dependent on the primary key.
c) Third Normal Form (3NF) - An entity is in 3NF if and only if it is in 2NF and every attribute that is not a part of the primary key is non-transitively dependent (mutually independent) on the primary key. Two or more attributes are mutually independent if none of them is functionally dependent on any combination of the others.

38. Normalization NORMALIZATION RULES
a) First Normal Form (1NF) - An entity is in 1NF if and only if all underlying simple domains contain single values only.
Matricule
Name
First Name
Sex
Chil first name
EMPLOYEE
A2783
Dupont
Alfred
Male
Léo, Léa, Lola
Matricule
Name
First name
Sex
EMPLOYEE
CHILDREN
First name
O,n
1,1
Be parent of
VALIDE
NON VALID

39. Normalization Class NORMALIZATION RULES
Second Normal Form (2NF) - An entity is in 2NF if and only if it is in 1NF and every non-key attribute is fully dependent on the primary key.
level-Section
Acces age
Date of evaluation
Room number
Class

40. Normalization NORMALIZATION RULES
Third Normal Form (3NF) - An entity is in 3NF if and only if it is in 2NF and every attribute that is not a part of the primary key is non-transitively dependent (mutually independent) on the primary key. Two or more attributes are mutually independent if none of them is functionally dependent on any combination of the others

41. Normalization Simplifying rule
Existence Dependency: A constraint between two related entities indicating that no instance of one (child entity) can exist without being related to an instance of the other (parent entity). The following relationship types represent existence dependencies: identifying relationships, categorization relationships and mandatory non-identifying relationships.
Functional Dependency: A special kind of integrity constraint that applies within the confines of a single entity “R”, where each “X” value of “R” has associated with it at most one “Y” value of “R” (at any one time). Attributes “X” and “Y” may be composite.
Name
First name
Adress
Student
Class
belong
1,1
1,n

42. MCD elaboration The steps
To draw up a list of the data starting from the documents of the company, and more generally of all the carriers data
To classify it these data alphabetically in order to sweep all on the regroupings properties
To carry out a priori the purification of the polysemes, the synonyms and the redundancies.
To locate the identifiers existing to release the natural objects
To attach to these objects the properties in functional dependence of their identifier
To place the relations and to attach if need be the functional properties in dependence to them several identifiers
To consider the remaining properties in order to gather them into object for which one will create the not formalized identifiers
To study the cardinalities of each couple entity-association,
Simplifier the model using the constraints of functional integrity,
Checking the model using the rules