Introduction%20to%20Modeling

1
Introduction to Modeling

• Extracted from textbook
• Object Oriented Modeling and Design with UML
• M. Blaha, J. Rumbaugh

2
What is a Model?

• Software Modeling plays an important role in
  software engineering.
• Current trends MDSE (Model Driven SE).
• A model is an abstraction of something for the
  purpose of understanding it before building it.
  Because a model omits nonessential details, it is
  easier to manipulate than the original entity. (A
  model is an abstract, simplified or incomplete
  description/representation of a part of the real
  word)

3
Modeling

• It is the process of creating models.
• Modeling is often practiced in all engineering
  disciplines.
• Modeling require a power of abstraction
• Persons that cannot THINK ABSTRACTLY fail to
  learn modeling skills.

4
Abstraction

• Selective examination of certain aspects of a
  problem or system.
• Goal
• Isolate those aspects that are important for some
  purpose and suppress those aspects that are not
  important essential versus details.
• Abstraction must always be for some purpose.
• Many different abstractions of the same system
  are possible depending on their purposes.

5
Abstraction

• Abstractions are incomplete and inaccurate.
• Dont search for absolute truth but for the
  adequacy for some purpose.
• A good model captures the crucial aspects of a
  problem and ignore the rest.

6
Why Modeling?

• Communication with customers
• Products engineers/architects build models to
  show to customers.
• Prototypes/Mock ups demonstration that imitate
  some of or all of the external behavior of a
  system

7
Why Modeling?

• Reduction of complexity
• The main reason for modeling is to deal with
  systems that are too complex to understand
  directly.
• The human mind cope with only a small amount of
  information at one time.
• Models reduce complexity by separating out a
  small number of important things to deal with at
  a time.

8
What to model?

• Real World Modeling
• Usage1 facilitate understanding of a problem in
  the real world without the intention of
  developing an application based on the model.
• Example1 Business process reengineering
  (business improvement goal)
• Example2 Requirement elicitation step (software
  development)
• Usage2 Develop an application that simulates
  the real world.
• Example Aircraft flight simulation
• Ref Object oriented real-world modeling
  revisited Sadahiro Isoda

9
What to model?

• Cyber Real World
• Usage Develop an application that automates
  business in the real world
• Examples
• Automating University library
• Automating Student Registration
• Ref Object oriented real-world modeling
  revisited Sadahiro Isoda

10
Modeling in SE

• Model-Driven Software Engineering (MDSE) based on
  the idea that SE life cycle phases produce and
  consume models.
• Models produced during a given phase will be
  consumed and used in next phases.
• Artifacts requirement models, analysis models,
  design models, testing models, implementation
  model (code).

11
Uses of Models in SE

• Models as sketches Developers find it useful to
  sketch descriptions of requirements, design or
  deployment concepts on whiteboards or paper when
  discussing their ideas with other developers or
  customer representatives
• Models as analysis artifacts Developers build
  analyzable models to check specified properties
  (e.g., consistency and satisfiability
  properties), to predict implementation qualities
  (e.g., performance), or to simulate implemented
  behavior
• Models as the basis for code generation or
  synthesis of software artifacts Models can be
  built for the purpose of generating
  implementations, test cases, deployment or
  software configuration scripts, or other software
  artifacts.

12
Modeling in SE

• It is useful to model a system from different but
  related viewpoints.
• Each viewpoint captures important aspects of the
  system.
• A combination of these viewpoints must capture a
  complete description of the system.
• Each model is intended to describe one
  aspect/viewpoint of a system but contains
  references to the other models.

13
Which viewpoints to model?

• Functional/process aspect.
• Structural/Data aspect
• Behavioral/Dynamic aspect
• Interaction/collaboration aspect

14
How to express Models?

• Need of modeling languages to express models.
• Modeling languages should be simple enough to be
  comprehensible and usable by modelers.
• Modeling languages should be expressive and
  abstract.

15
Typology of modeling languages

• Various criteria may be used to make a
  classification of modeling languages
• Textual versus diagram based syntax.
• General purpose or Domain based modeling
  languages