1. Traditional Approach to Requirements
ITEC 3010 “Systems Analysis and Design, I”
LECTURE 6:
Traditional Approach to Requirements
[Prof. Peter Khaiter]

2. Lecture Outline Traditional Approach vs. OOA Data Flow Diagrams (DFDs)
DFD and Levels of Abstraction
Context Diagrams ‏
DFD Fragments
Physical and Logical DFDs
Evaluating DFD Quality
Documentation of DFD Components
Locations and Communication Through Networks

3. Traditional Approach vs. OOA
Two approaches differ in the way the system is modeled and implemented:
• Traditional approach:
– views a system as a collection of processes (like computer programs, a set of instructions that execute in sequence)
– when the process executes it interacts with data (reads data values and then writes data values back to the data file
– emphasizes processes, data, inputs/outputs
• Object Oriented approach (OO):
– views a system as a collection of interacting objects which are capable of their own behavior (called methods) which allow the objects to interact with each other and with people using the system
– there are NO conventional processes and data files per se, just interacting objects

4. Traditional Approach vs. OO Approach

5. Requirements for the Traditional and OO Approaches

6. Data Flow Diagrams (DFDs)‏
Graphical system model that shows all main requirements for an IS in one diagram
Inputs/outputs
Processes
Data storage
Easy to read and understand with minimal training (only 5 symbols used)
DFD integrates processing triggered by events (event table) with the data entities modeled by ERD

7. DFD Symbols
The square is an external agent (a person or organization, outside the boundary of a system that provides data inputs or accepts data outputs)
The rectangle with rounded corners is a process (named “Look up item available” and can be referred to by its number, 1)
A process defines rules (algorithms or procedures) for transforming inputs into outputs
The lines with arrows are data flows (represents movement of data). Slide shows two data flows between Customer and process 1: a process input “Item inquiry” and process output named “Item availability details”
The flat three-sided rectangle is a data store (a file or part of a database that stores information about data entity)

8. Data Flow Diagram Symbols

9. DFD Fragment Showing Use Case Look Up Item Availability from the RMO

10. DFD Integrates Event Table and ERD

11. DFD and Levels of Abstraction
DFD is a modeling technique that breaks the system into a hierarchical set of increasingly more detailed models
DFD may reflect the processing at either a higher level (more general view of the system) or at lower level (a more detailed view of one process)
These different views of the system (higher level versus low level) creates the levels of abstraction
DFDs are decomposed into additional diagrams to provide multiple levels of detail
Higher-level diagrams provide general views of system
Lower-level diagrams provide detailed views of system

12. Layers of DFD Abstraction for Course Registration System

13. Context Diagrams
DFD that summarizes all processing activity for the system or subsystem
Highest level (most abstract) view of system
Shows system boundaries
System scope is represented by a single process, external agents, and all data flows into and out of the system

14. Context Diagrams for a Course Registration System

15. Notes on Context Diagrams
• Useful for showing system boundaries (represents the system scope within the single process plus external agents)
• External agents that supply or receive data from the system are outside the system scope
• Data stores are not usually shown in the context diagram since they are considered to be within the system scope
• It is the highest level of DFD
• Context diagram does not show any details of what takes place within the system

16. Context Diagrams for RMO CSS

17. DFD Fragments Created for each use case in the event table
Represent system response to one event within a single process symbol
Self-contained models
Focus attention on single part of system
Show only data stores required in the use case

18. Three Separate DFD Fragments for Course Registration System

19. Event-Partitioned System Model
DFD to model system requirements using single process for each use case/activity in system or subsystem
Combines all DFD fragments together to show decomposition of the context-level diagram
Shows the entire system on a single DFD (in greater detail than on the context diagram)
Sometimes called “diagram 0”
Used primarily as a presentation tool
Decomposed into more detailed DFD fragments

20. Combining DFD Fragments to Create Event- Partitioned System Model

21. Layers of DFD Abstraction

22. RMO Subsystems and Use Cases/Activities from Event Table

23. Context Diagram for RMO Order-Entry Subsystem

24. Five Separate DFD Fragments for RMO Order-Entry Subsystem

25. The event-partitioned model of the Order-Entry subsystem (diagram 0)

26. Decomposing DFD Fragments
Most DFD fragments can be further described using structured English
Sometimes DFD fragments need to be diagrammed in more detail
Decomposed into subprocesses in a detailed DFD
DFD numbering scheme
Hierarchical decomposition
DFD Fragment 2 is decomposed into Diagram 2
Diagram 2 has processes 2.1, 2.2, 2.3, 2.4 –four steps to complete the activity

27. Detailed DFD for Create new order DFD fragment

28. Hierarchy of the DFDs
• The top most - context diagram (entire system as one process), which breaks down to the subsystem diagram (one process per subsystem)
• The subsystem diagram is, in turn, decomposed into a set of the event-partitioned subsystem diagrams
• There is no single diagram 0. Instead, there is an event-partitioned DFD for each of the subsystems
• Each event-partitioned DFD is a diagram 0 for a single subsystem

29. Hierarchy of the DFDs

30. FIGURE 6-20 Incorrect and correct way to draw DFD.

31. Physical and Logical DFDs
Logical model
Assumes implementation in perfect technology
Does not tell how system is implemented
Physical model
Describes assumptions about implementation technology
Developed in last stages of analysis or in early design
E.g., the technology assumption is embedded in the name of process 1.1 “Making copies for department chairs” – it is a manual task, which implies that the data store “Old schedule” and the data flows into and out of process 1.1 are papers, etc.

32. Physical DFD for Scheduling Courses

33. Evaluating DFD Quality
Readable
Internally consistent and balanced
Accurately represents system requirements
Reduces information overload – rule of 7 +/- 2
Single DFD should not have more than 7 +/-2 processes
No more than 7 +/- 2 data flows should enter or leave a process or data store in a single DFD
Minimizes required number of interfaces

34. Data Flow Consistency Problems
Differences in data flow content between a process and its decomposition
Data outflows without corresponding inflows
Data inflows without corresponding outflows
Results in unbalanced DFDs

35. Black Hole and Miracle
black hole, i.e. a process with a data input that is never used to produce a data input. The following rules help to avoid the black holes:
       - All data that flow into a process must flow out of the process or be used to generated data that flow out of the process
        - All data that flow out of a process must have flowed into the process or have been generated from data that flowed into the process
Miracle - a process with a data output that is created out of nothing ( “miraculously appears”)

36. Unnecessary Data Input: Black Hole

37. Process with Impossible Data Output: a Miracle

38. Process with Unnecessary Data Input

39. Process with Impossible Data Output

40. Documentation of DFD Components
DFDs show three types of internal system component: processes, data flows and data stores
The details of each component need to be described
Lowest-level processes need to be described in detail
Data flow contents need to be described
Data stores need to be described in terms of data elements
Each data element needs to be described

41. Process Descriptions • Each process on a DFD must be formally defined
• There are several options for process definition including decomposition. In a process of decomposition, a higher-level process is formally defined by a DFD that contains lover-level processes, which, in turn, may be further decomposed into even lower-level DFDs. Eventually a point will be reached when a process becomes so simple that it can adequately be described by another process description method, i.e. without next lower-level DFD.
• These description methods include:
- Structured English
- Decision tables
- Decision trees
• These models describe the process as an algorithm.

42. Structured English Method of writing process specifications
Combines structured programming techniques with narrative English
Well-suited for lengthy sequential processes or simple control logic (single loop or if-then-else)‏
Ill-suited for complex decision logic or few (or no) sequential processing steps

43. Structured English Example

44. Process 2.1 and Structured English Process Description

45. A structured English process description for calculating shipping charges

46. Decision Tables and Decision Trees
Can summarize complex decision logic better than structured English
Incorporate logic into the table or tree structure to make descriptions more readable

47. Decision Table for Calculating Shipping Charges

48. Decision Tree for Calculating Shipping Charges

49. A Decision Table with Multiple Action Rows

50. Data Flow Definitions Data flow is a collection of data elements
Data flow definition is a textual description of data flow’s content and internal structure
Lists all the elements, e.g. a “New Order” data flow consists of Customer–Name, Customer-Address, Credit- Card-Information, Item-Number and Quantity
Often coincide with attributes of data entities included in ERD plus computed values
Algebraic notion is alternative to the list
Describes data elements on data flow plus data structure

51. List and Algebraic Notation for Data Flow Definition

52. RMO Products and Items Report

53. Data Flow Definition for RMO Products and Items Control Break Report

54. Data Element Definitions
Data type description
String, integer, floating point, Boolean
Sometimes very specific written description e.g., special codes (e.g. code A means ship immediately, code B – hold for one day and code C – hold shipment pending confirmation)
Length of element (usually for strings)
Maximum and minimum values (for numeric values)
Data dictionary – repository for definitions of data flows, data stores, and data elements

55. Data Element Definition Examples

56. Data Store Definitions
A data store on the DFD represents a data entity on the ERD (so, no separate definition is needed, just a note referring to the ERD for details)
If a data store are not linked to an ERD, a definition is provided as a collection of elements (like did for data flows)

57. Components of a Traditional Analysis Model
Four components of a traditional analysis model are
– Data flow diagrams
– Entity-relationship diagram
– Process definitions
– Data definitions
They form an interlocking set of specifications for system requirements
DFD shows highest-level view of the system
Other components describe some aspect of DFD
These models were created in the 1970’s and 1980’s as a part of the structured analysis methodology

58. Components of a Traditional Analysis Model

59. Locations and Communication Through Networks
Physical information needed during analysis
Number of user locations
Processing and data access requirements at various locations
Volume and timing of processing and data access requests
Needed to make initial design decisions such as
Distribution of computer systems, application software, database components, network capacity

60. Gathering Location Information
Identify locations where work is to be performed
Draw location diagram – a map that identifies all of the processing locations of a system (business offices, warehouses, manufacturing facilities)
List functions performed by users at each location
Build activity-location matrix - a table that describes the relationship between processes and the locations where they are performed
Rows are system activities from event table
Columns are physical locations
Build activity-data (CRUD) matrixis a table that describes stored data entities, the locations from which they are accessed and the nature of the access (i.e. which activities require access to the data). Source of this information is:
- the DFD fragments (traditional approach) and
- sequence diagrams (OO approach)
CRUD – create, read, update, and delete

61. RMO Location diagram

62. RMO Activity-Location Matrix

63. RMO Activity-Data Matrix (CRUD)‏

64. Readings
Today’s lecture: Chapter 6 – “The Traditional Approach to Requirements”
For next lecture: Chapter 7 – “The Object-Oriented Approach to Requirements”
Thank you !!!