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Lecture 9 ISM- © 2010 Houman Younessi Information Systems Spring 2011 Convener: Houman Younessi 1-860-548-7880 [email protected]

Lecture 9 ISM- © 2010 Houman Younessi Information Systems Spring 2011 Convener: Houman Younessi 1-860-548-7880 [email protected]

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Page 1: Lecture 9 ISM- © 2010 Houman Younessi Information Systems Spring 2011 Convener: Houman Younessi 1-860-548-7880 youneh@rpi.edu

Lecture 9

ISM- © 2010 Houman Younessi

Information Systems

Spring 2011

Convener:

Houman Younessi

1-860-548-7880

[email protected]

Page 2: Lecture 9 ISM- © 2010 Houman Younessi Information Systems Spring 2011 Convener: Houman Younessi 1-860-548-7880 youneh@rpi.edu

Lecture 9

A system is identified in terms of the single goal it is to achieve. A system name is a cognitive handle that allows the identification and communication of a particular coherent and purposeful set of activities. A system name is usually presented in the form of:

“A system to do/be/achieve X”

Example:

A system to generate birth certificates

A system to generate reusable components

A system to provide a uniform computing platform across government agencies

All these may actually refer to the same application software!

System

Page 3: Lecture 9 ISM- © 2010 Houman Younessi Information Systems Spring 2011 Convener: Houman Younessi 1-860-548-7880 youneh@rpi.edu

Lecture 9

Software Development is a form of System Development

System Development entails the processes of:

Finding out what is the problem

Arriving at a solution

Delivering on a good solution

Discovery

Invention

Construction

Page 4: Lecture 9 ISM- © 2010 Houman Younessi Information Systems Spring 2011 Convener: Houman Younessi 1-860-548-7880 youneh@rpi.edu

Lecture 9

Analysis

Design

Implementation

So “analysis and design” is all about identifying what the problem is and to propose one or several solutions to rectify the

problem.

What is the problem?

What is a solution?

How do we deliver on a good solution?

Discovery

Invention

Construction

Page 5: Lecture 9 ISM- © 2010 Houman Younessi Information Systems Spring 2011 Convener: Houman Younessi 1-860-548-7880 youneh@rpi.edu

Lecture 9

Figuring out the problem.

The problem that is to be figured out is immersed in the real world.

The real world (the problem situation) is a web of interactions of amazing complexity

To have a chance, we need to be able to focus only on what is:

RELEVANT

Page 6: Lecture 9 ISM- © 2010 Houman Younessi Information Systems Spring 2011 Convener: Houman Younessi 1-860-548-7880 youneh@rpi.edu

Lecture 9

We need therefore to concentrate on:

Those elements about which we need to ask questions,

Those elements about which we need to answer questions

We also need to make sure that:

Only those elements that are of our direct and immediate concern are focused on at any one time.

Page 7: Lecture 9 ISM- © 2010 Houman Younessi Information Systems Spring 2011 Convener: Houman Younessi 1-860-548-7880 youneh@rpi.edu

Lecture 9

The first of these is called:

The second is called:

CONTEXTUALIZATION

ABSTRACTION

Page 8: Lecture 9 ISM- © 2010 Houman Younessi Information Systems Spring 2011 Convener: Houman Younessi 1-860-548-7880 youneh@rpi.edu

Lecture 9

Once we have understood the problem, we need to:

Communicate our understanding:

To ourselves at a later time

To others

To do so, we need to capture, retain and communicate what is relevant and in context.

This is called Modeling

Page 9: Lecture 9 ISM- © 2010 Houman Younessi Information Systems Spring 2011 Convener: Houman Younessi 1-860-548-7880 youneh@rpi.edu

Lecture 9

Modeling is therefore a fundamental element of analysis and as such a vital part of software development.

In order to capture, retain and communicate what is needed, the modeler has to use a language. This is called:

The Modeling Language

The modeling language has to contain the vocabulary and the grammar of the modeling approach utilized.

Page 10: Lecture 9 ISM- © 2010 Houman Younessi Information Systems Spring 2011 Convener: Houman Younessi 1-860-548-7880 youneh@rpi.edu

Lecture 9

What’s there?

How does it happen?

When does it happen?

(or in what sequence?)

Things and static relationships

Change

Order and timing of change

Page 11: Lecture 9 ISM- © 2010 Houman Younessi Information Systems Spring 2011 Convener: Houman Younessi 1-860-548-7880 youneh@rpi.edu

Lecture 9

Things and static relationships

Change

Order and timing of change

Structure

Transformations

Causal (sequential) relationships

For all deterministic systems we must capture all that is relevant of these three aspects, if we are to have sufficient

understanding of them.

Page 12: Lecture 9 ISM- © 2010 Houman Younessi Information Systems Spring 2011 Convener: Houman Younessi 1-860-548-7880 youneh@rpi.edu

Lecture 9

System ModelingIn SE, we have an array of notations and diagrams for modeling in each of these three views.

Structure ModelingEntity Relationship Diagrams, Formal Structural Models (e.g. Z, Object Z or VDM), Class Diagrams,…

Transformational ModelingTransformational Relations(Functional Specification), Activity Diagrams , Data Flow Diagrams (with specification), Flow Charts, …

Causal (Dynamic) ModelingSequence Diagrams, Collaboration Diagrams, State-charts (State Transition Diagrams), Petri-nets, Entity Life Histories,…

Page 13: Lecture 9 ISM- © 2010 Houman Younessi Information Systems Spring 2011 Convener: Houman Younessi 1-860-548-7880 youneh@rpi.edu

Lecture 9

Structure modeling is modeling of things and their situational relationships. A photograph is a good structure model. It shows things that were there when the picture was taken and how they were situated with respect to one another.

We can similarly compose diagrams or other models of a problem situation in which we depict all the relevant things and relationships.

There are many ways to do this. We shall discuss the three most popular and prevalent of these. Namely:

Entity Relationship Modeling which is used mainly for database design

Formal Schemas and Formal Object Schemas (using Z and Object Z)

Class Diagrams (using UML) used mainly as part of object oriented modeling

Structure Modeling

Page 14: Lecture 9 ISM- © 2010 Houman Younessi Information Systems Spring 2011 Convener: Houman Younessi 1-860-548-7880 youneh@rpi.edu

Lecture 9

Entity Relationship (ER) Modeling:

This is an informal (or semi-formal) approach to structure modeling in which a situation is studied so that static and persistent elements in it are identified, along with their static relationships. A collection of like elements is called an entity. A mapping of elements of one entity onto another entity (or itself) is called a relationship.

Entities are defined in terms of a name and a set of attributes. Relationships are defined in terms of a verb phrase (e.g. works-for) that establishes the nature of the mapping between the entities.

The results of ER modeling are almost always shown using diagrams. There are many different conventions. In the absence of an industry standard, we use a popular one here of my preference.

Structure Modeling

Page 15: Lecture 9 ISM- © 2010 Houman Younessi Information Systems Spring 2011 Convener: Houman Younessi 1-860-548-7880 youneh@rpi.edu

Lecture 9

Example:Employee

Name:

SSN:

Salary:

DepartmentName:

Location:

Budget:

Works-Form 1

This means that there are many elements belonging to the set Employee (i.e. many persons employed) each is mapped into (has a relationship with) only one element belonging to the entity Department (a specific department). The relationship is that this particular employee works for one specific department. For each employee we keep his or her name, social security number and current salary. For each department we keep the name of the department, its location and its budget.

You have already learned this modeling approach earlier in the course.

Structure Modeling

Page 16: Lecture 9 ISM- © 2010 Houman Younessi Information Systems Spring 2011 Convener: Houman Younessi 1-860-548-7880 youneh@rpi.edu

Lecture 9

Formal Object Schemas: Object Z

Stack[T]max:N

items: seq T

#items max

INITitems = ‹ ›

Push( items)

#items < maxitems’ = ‹item?›⁀items

item?:T

Structure Modeling

Page 17: Lecture 9 ISM- © 2010 Houman Younessi Information Systems Spring 2011 Convener: Houman Younessi 1-860-548-7880 youneh@rpi.edu

Lecture 9

Pop( items)

item! ‹ ›items = ‹item!›⁀items’

item!:T

top( items)

item! ‹ ›items’ = items

item!:T

Structure Modeling

Page 18: Lecture 9 ISM- © 2010 Houman Younessi Information Systems Spring 2011 Convener: Houman Younessi 1-860-548-7880 youneh@rpi.edu

Lecture 9

There are many different approaches to causal modeling. Whilst they all attempt to do the same thing, they are not all of the same level of capability, formality, ease of use or learnability. In this course we cover a number of popular approaches to causal modeling, including:

Entity Life Histories

The UML suite of dynamic modeling facilities, which include

Petri-nets

Sequence diagrams

Collaboration diagrams

State diagrams

Causal Modeling

Page 19: Lecture 9 ISM- © 2010 Houman Younessi Information Systems Spring 2011 Convener: Houman Younessi 1-860-548-7880 youneh@rpi.edu

Lecture 9

Entity Life Histories

These are diagrams that depict the various states of a class or type of object from inception to demise. Usually used in relation to persistent database “entities”, they can become overwhelmed if the states are too numerous or the object can possess concurrent states. They also do not necessarily depict the events that lead to state transitions.

EMP

CREATE INIT UPDATE REPORT RETIRE ARCHIVE* *

Causal Modeling

Page 20: Lecture 9 ISM- © 2010 Houman Younessi Information Systems Spring 2011 Convener: Houman Younessi 1-860-548-7880 youneh@rpi.edu

Lecture 9

Transformation modeling is the third modeling view. It answers the question “how”.

Depending on level of granularity there are many techniques. Including:

Abstraction Level:

Dataflow Diagrams

Activity Diagrams

Low Level:

Pseudo-code

Flowcharts

etc.

Not part of UML

Transformational Modeling

Page 21: Lecture 9 ISM- © 2010 Houman Younessi Information Systems Spring 2011 Convener: Houman Younessi 1-860-548-7880 youneh@rpi.edu

Lecture 9

Flow charts

Flow charts depict the flow of control. They show how operations are performed and decisions made by depicting how the control in the program is exchanged from the beginning to the end of all paths of interest.

Flow charts show how the program works.

Flow charts are composed of a number of node types and one type of arc. The node types are:

Start/End node Transformation node Decision node Link node Special processing nodes Logic nodes

Transformational Modeling

Page 22: Lecture 9 ISM- © 2010 Houman Younessi Information Systems Spring 2011 Convener: Houman Younessi 1-860-548-7880 youneh@rpi.edu

Lecture 9

Flow charts can be high level or low level

High level flow charts depict the flow of control at a high level of granularity, such as the organization or the entire system. Low level ones usually depict the flow of control in a specific program unit.

The difference between a high level and low level flow chart is that in a low level flow chart all transformational nodes contain transformations that can not be usefully broken down to simpler flowcharts themselves. By this we mean doing so would produce transformation at a lower level of granularity than that of the target programming language.

Transformational Modeling

Page 23: Lecture 9 ISM- © 2010 Houman Younessi Information Systems Spring 2011 Convener: Houman Younessi 1-860-548-7880 youneh@rpi.edu

Lecture 9

Flow chart nodes:

Start/End nodes: These mark the beginning and end of a flow within a flowchart

Transformation nodes: These show a logical step taken

Terminator

Transformation Alternate transformation

Manual transformation

Transformational Modeling

Page 24: Lecture 9 ISM- © 2010 Houman Younessi Information Systems Spring 2011 Convener: Houman Younessi 1-860-548-7880 youneh@rpi.edu

Lecture 9

Decision nodes: These show alternate conditions or paths the flow may take

Link nodes: These connect various parts of the diagram (e.g. continue on next page)

Logic nodes: These are logical operators such as AND, OR and NOT

Condition

AND OR NOT

On page connector

Off page connector

Transformational Modeling

Page 25: Lecture 9 ISM- © 2010 Houman Younessi Information Systems Spring 2011 Convener: Houman Younessi 1-860-548-7880 youneh@rpi.edu

Lecture 9

Special processing nodes: These are nodes that depict specific large scale processing or machine interaction. Useful in the early days when flowcharting was amongst the only modeling methods available, they are now largely disused.

Manual input

Disk Other mag. storage

Stored data Punched tape Punched card

Seq. Access device

Console or display

Extract Merge Sort Collate Internal storage

Delay

Transformational Modeling

Page 26: Lecture 9 ISM- © 2010 Houman Younessi Information Systems Spring 2011 Convener: Houman Younessi 1-860-548-7880 youneh@rpi.edu

Lecture 9

Start

End

Read N

N>0

T

F

Read A,B

A=A+B N=N-1

N=0F

T

Write A

Transformational Modeling

Page 27: Lecture 9 ISM- © 2010 Houman Younessi Information Systems Spring 2011 Convener: Houman Younessi 1-860-548-7880 youneh@rpi.edu

Lecture 9

Data Flow DiagramsData flow diagrams depict the flow of data. They show how data received as input is changed to outputs by the various operations performed.

Data flow diagrams show how the data changes.

Basic data flow diagrams are composed of a number of node types and one type of arch. The node types are:

External Entities (Sources and Sinks) Processing node

Data-stores Link nodes

Transformational Modeling

Page 28: Lecture 9 ISM- © 2010 Houman Younessi Information Systems Spring 2011 Convener: Houman Younessi 1-860-548-7880 youneh@rpi.edu

Lecture 9

External entities (sources and Sinks): These are entities outside the scope of our focus that provide the inputs from the outside or receive the outputs generated. They are labeled by a noun or an object or class name.

Process nodes: These depict the processing that is done to the inputs into that process to form the output. Usually these nodes are labeled by a verb phrase representing the nature of the processing to be done and a number sequence depicting the process and its level

Customer

Book seatBook seat

1.4.71.4.7

Transformational Modeling

Page 29: Lecture 9 ISM- © 2010 Houman Younessi Information Systems Spring 2011 Convener: Houman Younessi 1-860-548-7880 youneh@rpi.edu

Lecture 9

Data-stores: These are buffers where interim outputs generated are stored for future usage. Data-stores are usually named.Link nodes: They connect the various parts of the diagrams to yield a less cluttered result. They are usually numbered or carry a symbol.

Primary Buffer

The only arc is called a dataflow and it depicts the flow of data (as input into or output from) an external entity or process. They are usually named.

client address

22

Transformational Modeling

Page 30: Lecture 9 ISM- © 2010 Houman Younessi Information Systems Spring 2011 Convener: Houman Younessi 1-860-548-7880 youneh@rpi.edu

Lecture 9

Example DFD

1.2.1

Validate Sell

1.2.2

Prepare SX Transaction

1.2.3

Register Transaction

Account

Invalid Req. Advice

Transaction A

dvice

Sell Validation

Trans. Confirmation

Sell Details

Account Update

Sell Advice

No. of Stock owned

Account Sell

Market Stock Price

Sell Stock; Level 3

Transformational Modeling

Page 31: Lecture 9 ISM- © 2010 Houman Younessi Information Systems Spring 2011 Convener: Houman Younessi 1-860-548-7880 youneh@rpi.edu

Lecture 9

Data Flow diagrams may depict a situation at multiple levels of granularity. By that we mean a process in a data flow diagram may be decomposed into an entire new dataflow diagram at a lower level, and so on. At each lower level, there will be more detail of the model visible. Conversely, one can say that a higher level process can be described in terms of a dataflow diagram composed of simpler, lower level processes, data flows and data-stores. However this decomposition process must stop at some stage. At that stage we shall still have a dataflow diagram that only depicts the transformation of inputs to outputs of various processes. It however does not say HOW each leaf level process should achieve this. This may be obvious but is not defined.

Transformational Modeling

Page 32: Lecture 9 ISM- © 2010 Houman Younessi Information Systems Spring 2011 Convener: Houman Younessi 1-860-548-7880 youneh@rpi.edu

Lecture 9

Dataflow diagrams are more so a mechanism for abstraction than a transformational modeling technique. They must be accompanied by a complementary mechanism that defines the leaf level transformations. Something like a flowchart of each leaf process, a pseudo-code, mathematical equation, truth table or formal definition is needed.

Important Note:

Transformational Modeling

Page 33: Lecture 9 ISM- © 2010 Houman Younessi Information Systems Spring 2011 Convener: Houman Younessi 1-860-548-7880 youneh@rpi.edu

Lecture 9

Pseudo-code:begin

Read r,a;

Declare x,y;

if { (a) L.T. 0

a=(-1)*a; };

Set x to r*sin(a);

Set y to r*cos(a);

Write x;

Write y;

end

Convert to Cartesian

1.5.6r

a

x

y

Transformational Modeling

Page 34: Lecture 9 ISM- © 2010 Houman Younessi Information Systems Spring 2011 Convener: Houman Younessi 1-860-548-7880 youneh@rpi.edu

Lecture 9

Mathematical expression:

)cos(

)sin(

ary

arx

Convert to Cartesian

1.5.6r

a

x

y

Desc. For 1.5.6

Transformational Modeling

Page 35: Lecture 9 ISM- © 2010 Houman Younessi Information Systems Spring 2011 Convener: Houman Younessi 1-860-548-7880 youneh@rpi.edu

Lecture 9

Activity diagrams depict the processing aspects of the system. They are similar to flowcharts except:

ACTIVITY DIAGRAMS

Activity charts allow synchronization

They are similar to dataflow diagrams except:

Transition between activities is via conditions not data. Activity charts allow synchronization

Transformational Modeling

Page 36: Lecture 9 ISM- © 2010 Houman Younessi Information Systems Spring 2011 Convener: Houman Younessi 1-860-548-7880 youneh@rpi.edu

Lecture 9

Order ProcessingFinance

Receive

Order

Receive

Supply

Select Outstanding order item

Assign Goods to

OrderAssign Item to Order

Reorder

Item Add Remainder

to Stock

Check Line Item

Cancel Order

Check order

Authorize payment

[failed][succeeded]

Dispatch Order [Stock assigned to all line items and payment

authorized]

*[for each line item on order]

* [for each chosen order item]

[in stock]

[all outstanding order items filled]

[notify supply]

[out of stock]

Stock Manager

Transformational Modeling

Page 37: Lecture 9 ISM- © 2010 Houman Younessi Information Systems Spring 2011 Convener: Houman Younessi 1-860-548-7880 youneh@rpi.edu

Lecture 9

Structure Transformation Causality

Objects

Classes

Relationships

Inputs

Outputs

Transformations

Events

States

Sequences

ENCAPSULATION

Page 38: Lecture 9 ISM- © 2010 Houman Younessi Information Systems Spring 2011 Convener: Houman Younessi 1-860-548-7880 youneh@rpi.edu

Lecture 9

UML has a an array of notations and diagrams for modeling in each of these three views.

Structure Modeling

Class notation, object notation, Associations, Links, Class diagrams, object diagrams,…

Transformational ModelingActors, Transformational relations, Use Case diagrams, Context Diagrams, Activity diagrams ,Transformational definitions, …

Page 39: Lecture 9 ISM- © 2010 Houman Younessi Information Systems Spring 2011 Convener: Houman Younessi 1-860-548-7880 youneh@rpi.edu

Lecture 9

Causal (Dynamic) Modeling

Events, Activities, Actions, Transitions, States, Sequence diagrams, Collaboration diagrams, Statechart diagrams, etc.…

In the next session we shall start with structural modeling and introduce some important elements of the UML

notation set.