Transcript ANALYZING REQUIREMENTS

Phase 2 – Systems
Analysis
Data and Process Modeling
Chapter 4
Second of four chapters in Systems Analysis Phase. It
explains how to represent system data and processes
graphically.
Objectives

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Describe data and process modeling
concepts and tools
Explain how structured analysis describes an
information system.
Describe the symbols used in data flow
diagrams.
Explain the sequence of data flow diagrams,
from general to specific.
Explain how to level and balance a set of
data flow diagrams.
Draw a complete set of data flow diagrams for
an information system.
Objectives

Describe how a data dictionary is used and
what it contains.
 Use process description tools, including
structured English, decision tables, and
decision trees.
 Explain the interaction among data flow
diagrams, the data dictionary, and process
description.
 Describe the relationship between logical and
physical models.
STRUCTURED ANALYSIS
Describes a system in terms of its
inputs, outputs , data and processes
 Analysts use data and process
modeling to show how system
processes transform data into useful
information
 End product is a logical model

– Shows what a system must do, regardless
of how it will be accomplished physically
STRUCTURED ANALYSIS
 IS
is large and complex
 Structured analysis provides
methods for analyzing,
organizing, controlling and
documenting large, complex
systems
STRUCTURED ANALYSIS
 Is
appropriate for business
information systems
–Data driven systems
 data
initiates procedures that
transform data from one form
into information
STRUCTURED ANALYSIS
 Document
IS data and data
transformations
 DATA FLOW
DIAGRAMS
 DATA DICTIONARY
 PROCESS DESCRIPTIONS
DATA FLOW DIAGRAMS
 Shows
how data moves and
changes through IS in graphical
top-down fashion
 essential model
 not used to show program logic
or detailed logic
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Process Symbol
A
PROCESS modifies, or
changes, data from one form to
another from.
 data is input to a process, the
process transforms data to
produce output data of a
different content or form
PROCESS
 Symbol
 Place
name of process inside the
symbol
 Name the process to identify the
function it accomplishes
 Name consists of active verb,
followed by singular noun
PROCESS SYMBOL

EXAMPLES
– PREPARE CHECKS
– POST CUSTOMER PAYMENTS
– CALCULATE TAXES
– DETERMINE PAST DUE
ACCOUNTS
– DETERMINE DEAN’S LIST
STUDENTS
PROCESS NAMES
 APPLY
PAYMENT
 CALCULATE PAYMENT
 ASSIGN FINAL GRADE
 VERIFY ORDER
 FILL ORDER
PROCESS
 Details
of process are not shown in
DFD
 Details of process are documented
in process description
 BLACK BOX in DFD
– We know general inputs, outputs and
functions, but not underlying details
Black Box approach
 allows
us to represent
processing flow of IS in a series
of increasingly detailed
diagrams without cluttering
more general diagrams with
unnecessary details
Data Flow Symbol
pathway by which data moves from one
part of the information system to
another part
 represents a specific piece of data or
set of data
 single data item – ex. name
 set of data -- class roster or processed
order

Data Flow Symbol
 Details
are not shown in DFD
 Details are defined in data
dictionary
Data Flow Symbol
 Symbol
for data flow is a line
segment with single arrowhead
 Line segment can be straight or
curved
 arrowhead indicates direction
the data flows
Data Flow Symbol
 Name
the dataflow to identify
the data it represents
 Name consists of adjectives (if
necessary) and singular noun
Data Flow Symbol
 Examples
–BANK DEPOSIT
–INVOICE PAYMENT
–STUDENT GRADE
–ORDER
–GRADING PARAMETERS ???
Combining Process and Data
Flow symbols
Process must act on an input, and
produce output
 Process must have at least 1 input data
flow and at least 1 output data flow

4-3
Combining Process and Data
Flow symbols
 Illegal
representations …
 Spontaneous Generation -Process that has no input
 Black hole -- Process that has no
output
 Gray hole -- has a least 1 input
and 1 output, input is insufficient to
generate output shown
4-4
Data Store Symbol
 data
repository
 when system must store data
because one or more processes
need to use the stored data at a
later time
 time length of storage is
unimportant
Data Store Symbol
 Symbol
is a flat rectangle that is
open on the right side and
closed on the left side
Data Store Symbol
 Place
name of data store
between lines
 Name data store to identify
category of data it contains
 Name consists of plural noun
and any supporting adjectives
Data Store Symbol

Examples
– STUDENTS
– ACCOUNTS RECEIVABLE
– PURCHASE ORDERS
– EMPLOYEES
Data Store Symbol
Must be connected to a process with a
data flow
 Must have at least 1 incoming data flow
 Must have at least 1 outgoing data flow
 Both incoming and outgoing data flows
must connect to a process

4-5
SOME DFD RULES
 Process
must have at least one
incoming and one outgoing data
flow
 Data flow must have one and
only one arrow head
SOME DFD RULES
 Data
store must be connected
to a data flow with a process at
the other end of data flow
 Data store must have at least
one incoming and one outgoing
data flow, with a process on the
other end
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EXTERNAL ENTITY
 Person,
department, outside
organization, or other IS that
provides data to the system or
receives data or information
from the system
EXTERNAL ENTITY
 Show
boundaries of the IS
 Interaction with the outside
world
 Terminators
 Source or Origin
 Destination or Sink
EXTERNAL ENTITY
 Symbol
is rectangle – usually
shaded
 Place name inside the rectangle
 Name is singular form of name of
department, outside organization,
other IS. or person (position, not
name)
EXTERNAL ENTITY
 Examples
– CUSTOMER
– STUDENT
– EMPLOYEE
– ACCOUNTING
– PAYROLL SYSTEM
– INTERNAL REVENUE SERVICE
EXTERNAL ENTITY
 SOURCE
 DESTINATION
 BOTH
4-7
Rules for External Entities
 Always
connected by a data
flow to a process
 External Entities are never
connected to each other
4-8
CONTEXT DIAGRAM
Top-level view of IS
 Shows boundaries and scope of IS
 Place one process symbol in center of
page
 Draw external entities around perimeter
of page
 Connect external entities to process
with data flows
 Do not show data stores – internal to IS

Context Diagram
 Determine
External Entities and
Data Flows
–Review IS requirements
–Identify External Entities
–Identify Name and content of
data flows
–Identify direction of data flow
Conventions for DFD’s
 One
Page
 Process name for context diagram
is name of system
 Process name for lower level
diagrams is active verb
 Unique names for each set of
symbols
Conventions for DFD’s
 Avoid
crossing lines
 Max of process symbols in one
diagram
–May duplicate external entity or
data store
–Document any duplication
 Use
abbreviated identifications
for Data Dictionary (process,
data store, external entity)
Context Diagram
 General
view of IS
 Entire IS represented by single
process symbol
Diagram 0
 Data
flow diagram that gives more
detailed view of IS
 show major processes, data flows,
and data stores for IS
 All external entities from Context
Diagram are on Diagram 0
Diagram 0
 Diagram
0 is more detailed
version of process 0
 Diagram 0 is EXPLODED
version of process 0
 Partitioned
 Decomposed
LEVELING DFD’s
 DFD
technique of representing
graphical model of IS first as a
single process, then in greater
and greater detail, until only
processes are functional
primitives
Functional Primitive
 Process
that consists of a
single function that is not
exploded further
LEVELING
 EXPLODING
, PARTITIONING,
DECOMPOSING the processes in
DFD’s
 DFD’s are top-down, general to
detail
 Each level shows increased detail
Leveling considerations
 Diagram
0 represents highest level
view of IS
 Larger more complex systems
need more levels
 Not all processes need to be
exploded same number of levels
Required symbols on
lower level DFD’s
 BALANCED
DFD’s -- parent
process’s input and output data
flows are preserved on child data
flow diagram
 Data stores on highest level DFD
that has 2 or more processes that
use that data store
DFD rules and lower level
diagrams
Notice that Customers data store has
outgoing data flow in diagram 1, but no
incoming data flow
 Is this OK???

DATA DICTIONARY
 Central
storehouse of data about IS
data and data transformations
 Use data dictionary throughout
SDLC and system operation
 Use data dictionary even if you
don’t use DFD’s
Data Dictionary
 Document
the contents of data
flows, data stores, external
entities and processes in DFD’s
 Data elements (smallest piece
of data with meaning in IS) -data item or field
Data elements in Data Dictionary
 Must
document every data element
 Alternate name -- synonym or alias
 Output format -- edit mask
 Prompt or column header -- field
caption
 Acceptable values -- domain
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Data Flows in Data Dictionary
 Must
document every data flow
 Abbreviation -- not identified
on DFD
 Record
 Origin / Destination
 Volume and frequency
Data stores in Data Dictionary
 Must
document every data store
 Data store name
 Abbreviation - matches DFD
 Record
 Input / Output data flows
 Volume and frequency
Processes in Data Dictionary
 Must
document every process that
is a FUNCTIONAL PRIMITIVE
 Process name
 Purpose
 Input / Output data flows
 Details later
External Entities
in Data Dictionary
Records in Data Dictionary
 Data
Elements logically
combined to form records
 Must document all records in
Data Dictionary
 Data element content - list all
elements included in record
Records in Data Dictionary
 data
element names must
match data elements in data
dictionary
 Primary key - uniquely identifies
a record PK
PROCESS DESCRIPTION TOOLS
 Documents
details of a
functional primitive
 details documented in precise,
concise manner
 One process description for
each functional primitive
PROCESS DESCRIPTION
SEQUENCE
SELECTION
ITERATION
STRUCTURED ENGLISH
 Uses
sequence, selection and
iteration
 Use indentation for readability
 Use limited vocabulary to
describe processing rules (IF,
FOR EACH, OUTPUT)
STRUCTURED ENGLISH
 similar
to pseudocode
 Process descriptions should be
understandable to end users
and system designers
 Captialized words are in data
dictionary
DECISION TABLES
 tabular
description of a
selection structure
 often better tool than structured
English for describing selection
process -- especially complex
structures
DECISION TABLE
DECISION TABLES
 Because
each condition is
either true or false, the number
of rules doubles each time you
add a condition
 Easy to construct and verify
DECISION TREES
 Graphical
representation of a
selection structure
 Form of a tree with the roots at the
left and branches to the right
 Presents same situation as
decision table
DECISION TREE
 Decision
table and Decision
Tree are equivalent
 Different form -- graph vs. table
 Tree has same number of end
branches as the table has
columns
Automated Structured Analysis
 CASE
tools reduce amount of
clerical work required to
organize and document IS
 minimize chance for error
Logical versus Physical Model
Logical model created during systems
analysis phase
 Logical model used as basis for
physical model
 Physical model created during systems
design phase
 Logical model describes what must
happen
 Physical model describes how it is to be
implemented

Softwear, Limited
Rick, SA and Carla, PA, continue their
work on the payroll project.
 Completed detailed interviews

– Understand how current system operates
– New requirements desired by users

Ready to organize findings and
documents with a logical model.
– Context Diagram
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4-46
New Century Health Clinic Case
Study
 Prepare
context diagram for New
Century’s information system
 Prepare diagram 0 for New Century
– 4 processes documented
– Include at least 1 data store
– Follow our DFD rules/conventions