Asi Chap008

SYSTEMS ANALYSIS AND DESIGN METHODS 5th Edition

Whitten Bentley Dittman

C H A P T E R

8
Irwin/McGraw-Hill

PROCESS
MODELING

Copyright © 2000 The McGraw-Hill Companies. All Rights reserved


Chapter Eight
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Process Modeling

Define systems modeling and differentiate between logical and physical system
models.
Define process modeling and explain its benefits.
Recognize and understand the basic concepts and constructs of a process model.
Read and interpret a data flow diagram.
Explain when to construct process models and where to store them.
Construct a context diagram to illustrate a system’s interfaces with its work
environment.
Identify use cases, external and temporal business events for a system.
Perform event partitioning and organize events in a functional decomposition
diagram.
Draw event diagrams and merge those events into a system diagram.
Draw primitive data flow diagrams and describe the elementary data flows and
processes in terms of data structures and procedural logic (Structured English and
decision tables), respectively.
Document the distribution of processes to locations.
Synchronize data and process models using a CRUD matrix.

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Chapter Map

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Models: Logical and Physical

A model is a representation of reality. Just as a
picture is worth a thousand words, most models are
pictorial representations of reality.
Logical models show
what a system is or does.
They are implementation
independent; that is, they
depict the system
independent of any
technical implementation.

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Physical models show not
only what a system is or
does, but also how the
system is (to be) physically
and technically implemented.
They are implementation
dependent because they
reflect technology choices.




Why Logical System Models

• Logical models remove biases that are the result of the
way the system is currently implemented, or the way
that any one person thinks the system might be
implemented.
• Logical models reduce the risk of missing business
requirements because we are too preoccupied with
technical results.
• Logical models allow us to communicate with endusers in nontechnical or less technical languages.
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Process Modeling and DFDs

Process modeling is a technique for organizing and
documenting the structure and flow of data through a
system’s processes, and/or the logic, policies, and
procedures to be implemented by a system’s processes.
A data flow diagram (DFD) is a tool (and type of process
model) that depicts the flow of data through a system and
the work or processing performed by that system.
DFDs have become a popular tool for business process
redesign.
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Simple Data Flow Diagram

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Differences Between DFDs and Flowcharts

• Processes on DFDs can operate in parallel (at-thesame-time)
– Processes on flowcharts execute one at a time

• DFDs show the flow of data through a system
– Flowcharts show the flow of control (sequence and
transfer of control)

• Processes on one DFD can have dramatically different
timing
– Processes on flowcharts are part of a single program
with consistent timing
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Systems Thinking

Systems thinking is the application of formal systems
theory and concepts to systems problem solving.
DFDs are a tool that supports systems thinking.

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Process Concepts

A process is work
performed on, or
in response to,
incoming data
flows or
conditions.
A
P ro c e s s

A System is a Process

in p u t
in p u t
in p u t

The
S y s te m
is a
P ro c e s s

o u tp u t
o u tp u t
o u tp u t

Feedack and
C o n tro l L o o p

T h e S y s t e m 's E n v ir o n m e n t
(c o n s ta n tly c h a n g in g )

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Decomposition

Decomposition is the
act of breaking a
system into its
component
subsystems,
processes, and
subprocesses. Each
level of abstraction
reveals more or less
detail.
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System Decomposition




Decomposition Diagrams

A decomposition
diagram or
hierarchy chart
shows the topdown, functional
decomposition of
a system.

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Types of Logical Processes

• A function is set of related and ongoing activities of a
business.
•
An event (or transaction) is a logical unit of work that
must be completed as a whole (as part of a function).
• An elementary process (or primitive process) is a
discrete, detailed activity or task required to respond to
an event. Usually, several such tasks must be
completed to respond to an event.

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Common Process Errors on DFDs

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Problems with Natural English
PROBLEMS WITH NATURAL ENGLISH 1

• Many of us do not write well, and we also tend not to question our writing abilities.
• Many of us are too educated! It’s often difficult for a highly educated person to communicate with an
audience that may not have had the same educational opportunities. For example, the average college
graduate (including most analysts) has a working vocabulary of 10,000 to 20,000 words; on the other hand,
the average non-college graduate has a working vocabulary of around 5,000 words.
• Some of us write everything like it was a program. If business procedures required such precision, we’d
write everything in a programming language.
• Too often, we allow the jargon and acronyms of computing to dominate our language.
• English statements frequently have an excessive or confusing scope. How would you carry out this
procedure: “If customers walk in the door and they do not want to withdraw money from their account or
deposit money to their account or make a loan payment, send them to the trust department.” Does this mean
that the only time you should not send the customer to the trust department is when he or she wishes to do
all three of the transactions? Or does it mean that if a customer does not wish to perform at least one of the
three transactions, that customer should not be sent to the trust department?
• We overuse compound sentences Consider the following procedure: “Remove the screws that hold the outlet
cover to the wall. Remove the outlet cover. Disconnect each wire from the plug, but first make sure the
power to the outlet has been turned off.” An unwary person might try to disconnect the wires prior to
turning off the power!
• Too many words have multiple definitions.
• Too many statements use imprecise adjectives. For example, an loan officer asks a teacher to certify that a
student is in good academic standing. What is good?
• Conditional instructions can be imprecise. For example, if we state that “all applicants under the age of 19
must secure parental permission,” do we mean less than 19, or less than or equal to 19?
• Compound conditions tend to show up in natural English. For example, if credit approval is a function of
several conditions: credit rating, credit ceiling, annual dollar sales for the customer in question, then
different combinations of these factors can result in different decisions. As the number of conditions and
possible combinations increases, the procedure becomes more and more tedious and difficult to write.
Irwin/McGraw-Hill

Source: Adapted from Matthies, Leslie, The New Playscript Procedure,
(Stamford, Companies. All Rights reserved
Copyright © 2000 The McGraw-Hill CT: Office Publications, Inc. 1977)



Structured English

Structured English is a language and syntax, based on the
relative strengths of structured programming and natural
English, for specifying the underlying logic of
elementary processes on DFDs.
1. For each CUSTOMER NUMBER in the data store CUSTOMERS:
a. For each LOAN in the data store LOANS that matches the above
CUSTOMER NUMBER:
1) Keep a running total of NUMBER OF LOANS for the
CUSTOMER NUMBER.
2) Keep a running total of thw ORIGINAL LOAN PRINCIPALfor the
CUSTOMER NUMBER.
3) Keep a running total of CURRENT LOAN BALANCE for the
CUSTOMER NUMBER.
4) Keep a running total of AMOUNTS PAST DUE for the
CUSTOMER NUMBER.
b. If the TOTAL AMOUNTS PAST DUE for the CUSTOMER NUMBER
is greater than $100.00 then:
1) Write the CUSTOMER NUMBER and all their data attributes
as described in the data flow LOANS AT RISK.
Else
1) Exclude the CUSTOMER NUMBER and data from the data
flow LOANS AT RISK.
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Structured English Constructs (Part 1)

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complex logic in which rows represent conditions

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Policies and Decision Tables

A policy is a set of rules that governs some process of
the business.
A decision table is a tabular form of presentation that
specifies a set of conditions and their corresponding
actions (as required to implement a policy).

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A Simple Decision Table

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Data Flows & Control Flows

• A data flow represents an input of data to a process, or
the output of data from a process.
– A data flow may also be used to represent the
creation, reading, deletion, or updating of data in a file
or database (called a data store).

– A composite data flow is a data flow that consists of
other data flows.

• A control flow represents a condition or nondata event
that triggers a process.
– Used sparingly on DFDs.
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Data Flow Packet Concept

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Composite and Elementary Data Flows

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Data Flows to and from Data Stores

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Illegal Data Flows

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Data Structures

Data flows can be defined by data structures.
A data structure is a specific arrangement of data
attributes that defines the organization of data contained
in a data flow.
A data attribute is the smallest piece of data that has
meaning to the end-users of a business.

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A Data Structure for a Data Flow
DATA STRUCTURE
ORDER=
ORDER NUMBER +
ORDER DATE+
[ PERSONAL CUSTOMER NUMBER,
CORPORATE ACCOUNT NUMBER]+
SHIPPING ADDRESS=ADDRESS+
(BILLING ADDRESS=ADDRESS)+
1 {PRODUCT NUMBER+
PRODUCT DESCRIPTION+
QUANTITY ORDERED+
PRODUCT PRICE+
PRODUCT PRICE SOURCE+
EXTENDED PRICE } N+
SUM OF EXTENDED PRICES+
PREPAID AMOUNT+
(CREDIT CARD NUMBER+EXPIRATION
DATE)
(QUOTE NUMBER)
ADDRESS=
(POST OFFICE BOX NUMBER)+
STREET ADDRESS+
CITY+
[STATE, MUNICIPALITY]+
(COUNTRY)+
POSTAL CODE

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ENGLISH ENTERPRETATION
An instance of ORDER consists of:
ORDER NUMBER and
ORDER DATE and
Either PERSONAL CUSTOMER NUMBER
or CORPORATE ACCOUNT NUMBER
and SHIPPING ADDRESS (which is equivalent
to ADDRESS)
and optionally: BILLING ADDRESS (which is
equivalent to ADDRESS)
and one or more instances of:
PRODUCT NUMBER and
PRODUCT DESCRIPTION and
QUANTITY ORDERED and
PRODUCT PRICE and
PRODUCT PRICE SOURCE and
EXTENDED PRICE
and SUM OF EXTENDED PRICES and
PREPAID AMOUNT and
optionally: both CREDIT CARD NUMBER and
EXPIRATION DATE
An instance of ADDRESS consists of:
optionally: POST OFFICE BOX NUMBER and
STREET ADDRESS and
CITY and
Either STATE or MUNICIPALITY
and optionally: COUNTRY
and POSTAL CODE



Data Structure Constructs
Data Structure

Format by Example
(relevant portion is boldfaced)

English Interpretation

Sequence of Attributes - The
WAGE AND TAX STATEMENT=
An instance of WAGE AND TAX STATEMENTS
sequence data structure indicates one
TAXPAYER IDENTIFICATION NUMBER+ consists of:
or more attributes that may (or must)
TAXPAYER NAME+
TAXPAYER IDENTIFICATION NUMBER and
be included in a data flow.
TAXPAYER ADDRESS+
TAXPAYER NAME and
WAGES, TIPS, AND COMPENSATION+
TAXPAYER ADDRESS and
FEDERAL TAX WITHHELD+…
WAGES, TIPS AND COMPENSATION and
FEDERAL TAX WITHHELD and…
Selection of Attributes - The
ORDER=
selection data structure allows you to
(PERSONAL CUSTOMER NUMBER,
show situations where different sets
CORPORATE ACCOUNT NUMBER)+
of attributes describe different
ORDER DATE+…
instances of the data flow.

An instance or ORDER consists of:
Either PERSONAL CUSTOMER NUMBER or
CORPORATE ACCOUNT NUMBER; and
ORDER DATE and…

Repetition of Attributes - The
CLAIM=
repetition data structure is used to set
POLICY NUMBER+
off a data attribute or group of data
POLICYHOLDER NAME+
attributes that may (or must) repeat
POLICY HOLDER ADDRESS+
themselves a specific number of time 0 {DEPENDENT NAME+
for a single instance of the data flow.
DEPENDENT’S RELATIONSHIP} N+
The minimum number of repetitions 1 {EXPENSE DESCRIPTION+
is usually zero or one.
SERVICE PROVIDER+
The maximum number of
EXPENSE AMOUNT} N
repetitions may be specified as “n”
meaning “many” where the actual
number of instances varies for each
instance of the data flow.

An instance of CLAIM consists of:
POLICY NUMBER and
POLICYHOLDER NAME and
POLICYHOLDER ADDRESS and
zero or more instance of:
DEPENDENT NAME and
DEPENDENT’S RELATIONSHIP and
one or more instances of:
EXPENSE DESCRIPTION and
SERVICE PROVIDER and
EXPENSE ACCOUNT

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Data Structure Constructs (concluded)

Data Structure

Format by Example

English Interpretation

Optional Attributes - The optional CLAIM=
notation indicates that an attribute, or POLICY NUMBER+
group of attributes in a sequence or
POLICYHOLDER NAME+
selection date structure may not be
POLICYHOLDER ADDRESS+
included in all instances of a data
( SPOUSE NAME+
flow.
DATE OF BIRTH)+…
Note: For the repetition data
structure, a minimum of “zero” is the
same as making the entire repeating
group “optional.”

An instance of CLAIM consists of:
POLICY NUMBER and
POLICYHOLDER NAME and
POLICYHOLDER ADDRESS and
optionally, SPOUSE NAME and
DATE OF BIRTH and...

Reusable Attributes - For groups of DATE=
attributes that are contained in many
MONTH+
data flows, it is desirable to create a
DAY+
separate data structure that can be
YEAR+
reused in other data structures.

Then, the reusable structures can be included in other
data flow structures as follows:
ORDER=ORDER NUMBER…+DATE
INVOICE=INVOICE NUMBER…+DATE
PAYMENT=CUSTOMER NUMBER…+DATE

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Data Types and Domains

Data attributes should be defined by data types and
domains.
A data type defines what class of data can be stored in an
attribute (e.g., character, integers, real numbers, dates,
pictures, etc.).
A domain defines what values or range of values an
attribute can legitimately take on.

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Diverging and Converging Data Flows

• A diverging data flow is one that splits into multiple
data flows.
– Useful for illustrating data that starts out naturally as
one flow, but needs to be routed to parallel processes.
– Also useful for illustrating multiple copies of the same
output going to different destinations.

•
A converging data flow is the merger of multiple data
flows into a single packet.
– Useful for illustrating data from multiple sources that
must come back together for some subsequent
processing
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Diverging and Converging Data Flows

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External Agents

• An external agent defines a person, organization unit,
or other organization that lies outside of the scope of
the project but that interacts with the system being
studied.
– External agents define the “boundary” or scope of a
system being modeled.
– As scope changes, external agents can become
processes, and vice versa.
– Almost always one of the following:
External
Agent

• Office, department, division inside the business but outside
the system scope.
• An external organization or agency.
• Another business or another information system.
• One of your system’s end-users or managers

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Data Stores

• A data store is an inventory of data.
– Frequently implemented as a file or database.
– A data store is “data at rest” compared to a data flow
that is “data in motion.”
– Almost always one of the following:
• Persons
(or groups of persons)
• Places
• Objects
• Events
(about which data is captured)
• Concepts
(about which data is important)

Data
Store

– Data stores depicted on a DFD store all instances of
data entities (depicted on an ERD)
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When to Draw Process Models

• Strategic systems planning
– Enterprise process models illustrate important
business functions.

• Business process redesign
– “As is” process models facilitate critical analysis.
– “To be” process models facilitate improvement.

• Systems analysis (primary focus of this course)
– Model the existing system including its limitations
– Model the target system’s logical requirements
(meaning processes and data flows needed regardless
of how the system will be implemented)
– Model candidate technical solutions (physical DFDs
only)
– Model the target technical solution (physical DFDs
only)
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Classical Structured Analysis
1. Draw top-down physical DFDs that represent the current
physical implementation of the system including its limitations.
2. Convert the physical DFDs to their logical equivalents.
3. Draw top-down logical DFDs that represent an improved
system.
4. Describe all data flows, data stores, policies, and procedures in
a data dictionary or encyclopedia.
5. Optionally, mark up copies of the logical DFDs to represent
alternative physical solutions.
6. Draw top-down physical DFDs that represent the target
solution.
THE ABOVE METHODOLOGY IS RARELY PRACTICED
ANYMORE BECAUSE IT IS VERY CUMBERSOME AND
TIME-CONSUMING.
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Modern Structured Analysis
1. Draw a context DFD to establish initial project scope.
2. Draw a functional decomposition diagram to partition the
system into subsystems.
3. Create an event-response or use-case list for the system to
define events for which the system must have a response.
4. Draw an event DFD (or event handler) for each event.
5. Merge event DFDs into a system diagram (or, for larger
systems, subsystem diagrams).
6. Draw detailed, primitive DFDs for the more complex event
handlers.
7. Document data flows and processes in the data dictionary.
THE ABOVE METHODOLOGY, BASED ON EVENT
PARTITIONING, IS MORE COMMONLY PRACTICED.
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Structured Analysis Diagram Progression

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(1 of 3)





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(2 of 3)





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(3 of 3)




CASE for DFDs (Sample Screen)

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from System Architect 2001




SoundStage Context DFD
Accounts
Receivable

Promotion

Club
Member

Member Order

Member
Credit
Status
Warehouse

Potential
Member

various Inquiry Reponses
New Subscription
Subscription Offer

Member
Services
System

Revised Packing Order
New Promotion
Subscription Program
various Sales Reports

Subscription Renewal

various
Promotion Reports

Marketing
Department

various Subscription Reports
Past
Member

Resubscription Offer
various Member
Reports

Irwin/McGraw-Hill

Member
Services




SoundStage Functional Decomposition Diagram
Member
Services
System

Subscription
Subsystem

Promotion
Subsystem

Order
Subsystem

Operations
Subsystem

Process
Subscription
Transactions

Process
Promotion
Transactions

Process
Order
Transactions

Process
Membership
Transactions

Generate
Subscription
Reports

Generate
Promotion
Reports

Generate
Order
Reports

Process
Marketing
Transactions

Process
Warehouse
Transactions

Irwin/McGraw-Hill




Events

• Events define processes needed to respond to those
events.
– External events are those initiated by external agents.
They result in an input transaction or data flow.
– Temporal events are those that are triggered by the
passage of time. They simply “happen” and are
indicated by a control flow.
– State events are those based on a system’s change
from one state to another.

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Use Cases

• Use cases are based upon object-oriented concepts that
are essentially the same as events.
– Use case analysis is the process of identifying and
modeling business events and how the system
responds to them.
– An actor is anything that needs to interact with the
system (essentially, a synonym for external agent).

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Use Case List
Actor

Event (or Use Case)

Trigger

Responses

Marketing

Establishes a new
membership subscription plan
to entice new members.

NEW MEMBER SUBSCRIPTION
PROGRAM

Generate SUBSCRIPTION
PLAN CONFIRMATION.
Create AGREEMENT in the
database.

Marketing

Establishes a new
membership resubscription
plan to lure back former
members.

PAST MEMBER
RESUBSCRIPTION PROGRAM

Generate SUBSCRIPTION
PLAN CONFIRMATION.
Create AGREEMENT in the
database.

Marketing

Changes a subscription plan
for current members (e.g.,
extending the fulfillment
period)

SUBSCRIPTION PLAN
CHANGE.

Generate AGREEMENT

A subscription plan expires.

(current date)

(time)

CHANGE CONFIRMATION.

Update AGREEMENT in the
database.
Generate AGREEMENT

Logically Delete (void)
AGREEMENT in the database.

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Use Case List (continued)
Actor

Event (or Use Case)

Marketing

Cancels a subscription plan
before its planned expiration

Trigger

Responses
Generate

CANCELATION


Logically Delete (void)
AGREEMENT in the database.
Member

Joins the club by subscribing.
(“Take any 12 CDs for one
penny and agree to buy 4
more at regular prices within
two years.”)

NEW SUBSCRIPTION

Generate MEMBER
DIRECTORY UPDATE
CONFIRMATION.

Create MEMBER in the
database.
Create first MEMBER ORDER
MEMBER ORDERED
PRODUCTs in the database.

Member

hanges address
(including email and privacy
code)

CHANGE OF ADDRESS

Generate MEMBER
DIRECTORY UPDATE
CONFIRMATION.

Update MEMBER in the
database.

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Use Case List (continued)

Actor

Event (or Use Case)

Trigger

Responses

Accounts
Receivable

Changes member’s credit
status

CHANGE OF CREDIT STATUS

Generate CREDIT
DIRECTORY UPDATE
CONFIRMATION.

Update MEMBER in the
database.
(time)

90 days after a Marketing
decides to no longer sell a
product.

(current date)

Generate CATALOG CHANGE
CONFIRMATION.
Logically Delete
(deactivate) PRODUCT in the
database.

Member

Wants to pick products for
possible purcase.
(Logical requirement is driven
by vision of web-based access

PRODUCT INQUIRY

Generate CATALOG
DESCRIPTION.

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Event Decomposition Diagram (partial)
Member
Services
System

Subscription
Subsystem

Process
Subscription
Transactions

Generate
Subscription
Reports

Promotion
Subsystem

Process
Promotion
Transactions

Generate
Promotion
Reports

Order
Subsystem

Process
Order
Transactions

Generate
Order
Reports

Process
Membership
Transactions

Pg
3

Pg
2

Process
Marketing
Transactions

Process
Warehouse
Transactions

Pg
4

Generate
Quarterly
Subscription
Report

Process
New
Subscription
Plan

Operations
Subsystem

Generate
Inactive
Member
Report

Generate
Agreement
Compliance
Report

Generate
Membership
Directory

Generate
Subscription
Analysis
Report

Process
New
Resubscription Plan

Process
Change
to a
Subscription
Plan

Process
Subscription
Plan Expiration

Process
Subscription
Plan
Cancelation

Process New
Member
Subscription

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Process
Former
Member
Resubscription

Process
Member
Change of
Address

Process
Member
Change of
Preferences




External Event DFD

Club
Member

Member Change
of Address

Process
Member
Address
Change

Updated
Member
Address

Members

Member Updated Address Confirmation

Irwin/McGraw-Hill




External Event DFD (more complex)
Members

Updated Member
from Order

Accounts
Receivable
Relevant
Transactions

Member

Club Member

Member Order

Process
Member
Order

Member
Order
Confirmation

Member
Orders

Member
Ordered
Products

Irwin/McGraw-Hill

New
Member
Order
New
Member
Ordered
Products

Warehouse
Packing Order

Inventory Commitment
Product
and
Availability

Products




Temporal Event DFD
Agreements

Members

Fulfillment
Progress

Calendar
End of Month

Irwin/McGraw-Hill

Agreement

Identify
Agreements
Near
Default

Agreement
Default
Exception
Report

Agreements
Manager



System DFD


(see book for more readable copy)

Transactions

Product and Availability
Products
Product and
Availability
Relevant
Transactions

Member

Member Order

Process
Member Order

Inventory Commitment

Inventory
Commitmen
t

Member

Subscription Order
Warehouse

Packing Order
Process
Subscription
Order

Packing Order

Member Order
Confirmation

Subscription
Order
Confirmation

New Member
Ordered Products
Member
Updated Member
from Order
Members

New
Member
Order

New Member
Ordered
Products

Address

New Member Order
Members
Member Orders

Member Ordered
Products

Member Orders

Deleted
Member
Order

Orders

Updated
Member

Updated
Member
Order
Updated Member
from Updated Order
Member
Order
Change
Request

Deleted Member
Ordered Products
Ordered
Products

Member

Member Order Confirmation

Process
Member Order
Revision

Generate
Order Analysis
Report

Process
Member Order
Cancelation

Updated
Member
Ordered
Products

Product and
Availability

Member Order
Cancelation

Member

Member
Order
Cancelation
Notice

End of Day

Inventory
Commitment
Revised
Packing Order

Warehouse

Time

Order
Analysis
Report

Club
Directors

Products

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Primitive DFD (see book for more readable copy)
Member ID
and Address

Member

Validate
Member

Members

Updated Member from Order

Invalid Member ID
Invalid Product ID

Invalid
Order

Ordered
Product ID

Validate
Ordered
Product

Product

Valid
Product
Ordered
Product
Quantity

Member
Member Order

Check Product
Availability

Products
Product Availability
Inventory Comittment

Available
Product
Bonus
Credits
Claimed

Product Price

Calculate
Order Cost

Cost to
Member
Payment
Credit Problem and Instruction

Relevant
Transactions
Order to be Filled

Member Orders
Member Ordered
Products

Members

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Credit Details

Check Member
Credit

Confirmed Member Order

New
Member
Order
New Member
Ordered Products

Transactions

Order to be Filled

Record Order

Release Order

Packing
Order

Warehouse

Updated Credits




Data Structure for a Primitive Data Flow

Data Flow
Data
Structure

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Logic for a Primitive Process
Process
Logic

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8.30 Data to Process CRUD Matrix

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8.31 Process to Location Association Matrix

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