Process Modeling: C H A P T E R
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SYSTEMS ANALYSIS AND DESIGN METHODS 5th Edition
Whitten Bentley Dittman
C H A P T E R
8
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PROCESS MODELING
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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.
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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
A System is a Process
i n p u t i n p u t i n p u t
T h S y s i s P r o
e t e m a c e s s
o u t p u t o u t p u t o u t p u t
F e e d a c k a n d C o n t r o l L o o p
r o c e s s
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T h e S y s t e m 's E n v i r o n m ( c o n s t a n t l y c h a n g i n g )
e n t
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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
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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.
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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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Structured English Constructs (Part 2)
complex logic in which rows represent conditions
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Structured English Constructs (Part 3)
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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 ENGLISH ENTERPRETATION
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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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
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Data Structure Constructs Data Structure
Format by Example (relevant portion is boldfaced)
English Interpretation (relevant portion is boldfaced)
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 (relevant portion is boldfaced)
English Interpretation (relevant portion is boldfaced)
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: • Office, department, division inside the business but outside the system scope. • An external organization or agency. • Another business or another information system. External • One of your system’s end-users or managers Agent
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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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Structured Analysis Diagram Progression
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(2 of 3)
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Structured Analysis Diagram Progression
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(3 of 3)
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CASE for DFDs (Sample Screen)
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SoundStage Context DFD Accounts Receivable
Promotion
Club Member
Member Order
Member Credit Status Warehouse
Potential Member
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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
Member Services
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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
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Process Warehouse Transactions
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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)
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CHANGE CONFIRMATION.
Update AGREEMENT in the database. Generate AGREEMENT CHANGE CONFIRMATION.
Logically Delete (void) AGREEMENT in the database.
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Use Case List (continued) Actor
Event (or Use Case)
Trigger
Marketing
Cancels a subscription plan before its planned expiration
Responses Generate
CANCELATION
CHANGE CONFIRMATION.
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
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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
Order Subsystem
Process Order Transactions
Generate Promotion Reports
Process Marketing Transactions
Process Warehouse Transactions
Pg 4
Generate Quarterly Subscription Report
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 Membership Transactions
Pg 3
Pg 2
Process New Subscription Plan
Generate Order Reports
Operations Subsystem
Process Former Member Resubscription
Process Member Change of Address
Process Member Change of Preferences
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External Event DFD
C lu b M em ber
M em ber C hange o f A d d re s s
P ro c e s s M em ber A d d re s s C hange
U p d a te d M em ber A d d re s s
M e m b e rs
M e m b e r U p d a te d A d d re ss C o n firm a tio n
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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
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New Member Order
Warehouse Packing Order
Inventory Commitment
New Member Ordered Products
Product and Availability
Products
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Temporal Event DFD Agreements
Members
Fulfillment Progress
Calendar
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End of Month
Agreement
Identify Agreements Near Default
Agreement Default Exception Report
Agreements Manager
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System DFD
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(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 Process Member Order Revision
Member Order Confirmation
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
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Data Structure for a Primitive Data Flow
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Data Flow Data Structure
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Logic for a Primitive Process
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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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C H A P T E R
8
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PROCESS MODELING
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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.
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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
A System is a Process
i n p u t i n p u t i n p u t
T h S y s i s P r o
e t e m a c e s s
o u t p u t o u t p u t o u t p u t
F e e d a c k a n d C o n t r o l L o o p
r o c e s s
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T h e S y s t e m 's E n v i r o n m ( c o n s t a n t l y c h a n g i n g )
e n t
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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
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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.
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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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Structured English Constructs (Part 2)
complex logic in which rows represent conditions
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Structured English Constructs (Part 3)
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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 ENGLISH ENTERPRETATION
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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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
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Data Structure Constructs Data Structure
Format by Example (relevant portion is boldfaced)
English Interpretation (relevant portion is boldfaced)
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 (relevant portion is boldfaced)
English Interpretation (relevant portion is boldfaced)
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: • Office, department, division inside the business but outside the system scope. • An external organization or agency. • Another business or another information system. External • One of your system’s end-users or managers Agent
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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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Structured Analysis Diagram Progression
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(2 of 3)
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Structured Analysis Diagram Progression
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(3 of 3)
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CASE for DFDs (Sample Screen)
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SoundStage Context DFD Accounts Receivable
Promotion
Club Member
Member Order
Member Credit Status Warehouse
Potential Member
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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
Member Services
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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
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Process Warehouse Transactions
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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)
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CHANGE CONFIRMATION.
Update AGREEMENT in the database. Generate AGREEMENT CHANGE CONFIRMATION.
Logically Delete (void) AGREEMENT in the database.
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Use Case List (continued) Actor
Event (or Use Case)
Trigger
Marketing
Cancels a subscription plan before its planned expiration
Responses Generate
CANCELATION
CHANGE CONFIRMATION.
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
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hanges address (including email and privacy code)
CHANGE OF ADDRESS
Generate MEMBER DIRECTORY UPDATE CONFIRMATION.
Update MEMBER in the database.
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SYSTEMS ANALYSIS AND DESIGN METHODS 5th Edition
Whitten Bentley Dittman
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.
Irwin/McGraw-Hill
Copyright © 2000 The McGraw-Hill Companies. All Rights res
SYSTEMS ANALYSIS AND DESIGN METHODS 5th Edition
Whitten Bentley Dittman
Event Decomposition Diagram (partial) Member Services System
Subscription Subsystem
Process Subscription Transactions
Generate Subscription Reports
Promotion Subsystem
Process Promotion Transactions
Order Subsystem
Process Order Transactions
Generate Promotion Reports
Process Marketing Transactions
Process Warehouse Transactions
Pg 4
Generate Quarterly Subscription Report
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
Irwin/McGraw-Hill
Process Membership Transactions
Pg 3
Pg 2
Process New Subscription Plan
Generate Order Reports
Operations Subsystem
Process Former Member Resubscription
Process Member Change of Address
Process Member Change of Preferences
Copyright © 2000 The McGraw-Hill Companies. All Rights res
SYSTEMS ANALYSIS AND DESIGN METHODS 5th Edition
Whitten Bentley Dittman
External Event DFD
C lu b M em ber
M em ber C hange o f A d d re s s
P ro c e s s M em ber A d d re s s C hange
U p d a te d M em ber A d d re s s
M e m b e rs
M e m b e r U p d a te d A d d re ss C o n firm a tio n
Irwin/McGraw-Hill
Copyright © 2000 The McGraw-Hill Companies. All Rights res
SYSTEMS ANALYSIS AND DESIGN METHODS 5th Edition
Whitten Bentley Dittman
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
Warehouse Packing Order
Inventory Commitment
New Member Ordered Products
Product and Availability
Products
Copyright © 2000 The McGraw-Hill Companies. All Rights res
SYSTEMS ANALYSIS AND DESIGN METHODS 5th Edition
Whitten Bentley Dittman
Temporal Event DFD Agreements
Members
Fulfillment Progress
Calendar
Irwin/McGraw-Hill
End of Month
Agreement
Identify Agreements Near Default
Agreement Default Exception Report
Agreements Manager
Copyright © 2000 The McGraw-Hill Companies. All Rights res
SYSTEMS ANALYSIS AND DESIGN METHODS 5th Edition
System DFD
Whitten Bentley Dittman
(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 Process Member Order Revision
Member Order Confirmation
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
Irwin/McGraw-Hill
Copyright © 2000 The McGraw-Hill Companies. All Rights res
SYSTEMS ANALYSIS AND DESIGN METHODS 5th Edition
Whitten Bentley Dittman
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
Irwin/McGraw-Hill
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
Copyright © 2000 The McGraw-Hill Companies. All Rights res
SYSTEMS ANALYSIS AND DESIGN METHODS 5th Edition
Whitten Bentley Dittman
Data Structure for a Primitive Data Flow
Irwin/McGraw-Hill
Data Flow Data Structure
Copyright © 2000 The McGraw-Hill Companies. All Rights res
SYSTEMS ANALYSIS AND DESIGN METHODS 5th Edition
Whitten Bentley Dittman
Logic for a Primitive Process
Irwin/McGraw-Hill
Process Logic
Copyright © 2000 The McGraw-Hill Companies. All Rights res
SYSTEMS ANALYSIS AND DESIGN METHODS 5th Edition
Whitten Bentley Dittman
8.30 Data to Process CRUD Matrix
Irwin/McGraw-Hill
Copyright © 2000 The McGraw-Hill Companies. All Rights res
SYSTEMS ANALYSIS AND DESIGN METHODS 5th Edition
Whitten Bentley Dittman
8.31 Process to Location Association Matrix
Irwin/McGraw-Hill
Copyright © 2000 The McGraw-Hill Companies. All Rights res
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