1. SYSTEM MODELS MUHAMMAD RIZWAN

2. Objectives  To explain why the context of a system should be modelled as part of the RE process  To describe behavioural modelling, data modelling and object modelling  To introduce some of the notations used in the Unified Modeling Language (UML)  To show how CASE workbenches support system modelling

3. Topics covered  Context models  Behavioural models  Data models  Object models  CASE workbenches

4. System modelling  System modelling helps the analyst to understand the functionality of the system and models are used to communicate with customers.  Different models present the system from different perspectives  External perspective showing the system’s context or environment;  Behavioural perspective showing the behaviour of the system;  Structural perspective showing the system or data architecture.

5. Model types  Data processing model showing how the data is processed at different stages.  Composition model showing how entities are composed of other entities.  Architectural model showing principal sub-systems.  Classification model showing how entities have common characteristics.  Stimulus/response model showing the system’s reaction to events.

6. Context models  Context models are used to illustrate the operational context of a system - they show what lies outside the system boundaries.  Social and organisational concerns may affect the decision on where to position system boundaries.  Architectural models show the system and its relationship with other systems.

7. The context of an ATM system

8. Process models  Process models show the overall process and the processes that are supported by the system.  Data flow models may be used to show the processes and the flow of information from one process to another.

9. Equipment procurement process

10. Behavioural models  Behavioural models are used to describe the overall behaviour of a system.  Two types of behavioural model are:  Data processing models that show how data is processed as it moves through the system;  State machine models that show the systems response to events.  These models show different perspectives so both of them are required to describe the system’s behaviour.

11. Data-processing models  Data flow diagrams (DFDs) may be used to model the system’s data processing.  These show the processing steps as data flows through a system.  DFDs are an intrinsic part of many analysis methods.  Simple and intuitive notation that customers can understand.  Show end-to-end processing of data.

12. Order processing DFD

13. Data flow diagrams  DFDs model the system from a functional perspective.  Tracking and documenting how the data associated with a process is helpful to develop an overall understanding of the system.  Data flow diagrams may also be used in showing the data exchange between a system and other systems in its environment.

14. Data Flow Diagram  Squares representing external entities, which are sources or destinations of data.  Rounded rectangles representing processes, which take data as input, do something to it, and output it.  Arrows representing the data flows, which can either be electronic data or physical items.  Open-ended rectangles representing data stores, including electronic stores such as databases or XML files and physical stores such as or filing cabinets or stacks of paper.

15. Creating Data Flow Diagrams Steps: 1.Create a list of activities 2.Construct Context Level DFD (identifies external entities and processes) 3.Construct Level 0 DFD (identifies manageable sub process ) 4.Construct Level 1- n DFD (identifies actual data flows and data stores ) 5.Check against rules of DFD

16. DFD Naming Guidelines  External Entity  Noun  Data Flow  Names of data  Process  verb phrase  a system name  a subsystem name  Data Store  Noun

17. Creating Data Flow Diagrams Lemonade Stand Example

18. Creating Data Flow Diagrams Steps: 1.Create a list of activities Old way: no Use-Case Diagram New way: use Use-Case Diagram 2.Construct Context Level DFD (identifies sources and sink) 3.Construct Level 0 DFD (identifies manageable sub processes ) 4.Construct Level 1- n DFD (identifies actual data flows and data stores ) Example The operations of a simple lemonade stand will be used to demonstrate the creation of dataflow diagrams.

19. Creating Data Flow Diagrams 1.Create a list of activities Example Think through the activities that take place at a lemonade stand. Customer Order Serve Product Collect Payment Produce Product Store Product

20. Creating Data Flow Diagrams Example Also think of the additional activities needed to support the basic activities. Customer Order Serve Product Collect Payment Produce Product Store Product Order Raw Materials Pay for Raw Materials Pay for Labor 1.Create a list of activities

21. Creating Data Flow Diagrams Example Group these activities in some logical fashion, possibly functional areas. Customer Order Serve Product Collect Payment Produce Product Store Product Order Raw Materials Pay for Raw Materials Pay for Labor 1.Create a list of activities

22. Creating Data Flow Diagrams 0.0 Lemonade System EMPLOYEECUSTOMER Pay Payment Order Context Level DFD Example Create a context level diagram identifying the sources and sinks (users). Customer Order Serve Product Collect Payment Produce Product Store Product Order Raw Materials Pay for Raw Materials Pay for Labor VENDOR Payment Purchase Order Production Schedule Received Goods Time Worked Sales Forecast 2.Construct Context Level DFD (identifies sources and sink) Product Served

23. Creating Data Flow Diagrams Level 0 DFD Example Create a level 0 diagram identifying the logical subsystems that may exist. Customer Order Serve Product Collect Payment Produce Product Store Product Order Raw Materials Pay for Raw Materials Pay for Labor 3.Construct Level 0 DFD (identifies manageable sub processes ) 2.0 Production EMPLOYEE Production Schedule 1.0 Sale 3.0 Procure- ment Sales Forecast Product Ordered CUSTOMER Pay Payment Customer Order VENDOR Payment Purchase Order Order Decisions Received Goods Time Worked Inventory Product Served 4.0 Payroll

24. Creating Data Flow Diagrams Level 1 DFD Example Create a level 1 decomposing the processes in level 0 and identifying data stores. 4.Construct Level 1- n DFD (identifies actual data flows and data stores ) 1.3 Produce Sales Forecast Sales Forecast Payment Customer Order Serve Product Collect Payment Produce Product Store Product Order Raw Materials Pay for Raw Materials Pay for Labor 1.1 Record Order Customer Order ORDER 1.2 Receive Payment PAYMENT Severed Order Request for Forecast CUSTOMER

25. Creating Data Flow Diagrams Level 1 DFD Example Create a level 1 decomposing the processes in level 0 and identifying data stores. 4.Construct Level 1 (continued) Customer Order Serve Product Collect Payment Produce Product Store Product Order Raw Materials Pay for Raw Materials Pay for Labor 2.1 Serve Product Product Order ORDER 2.2 Produce Product INVENTORTY Quantity Severed Production Schedule RAW MATERIALS 2.3 Store Product Quantity Produced & Location Stored Quantity Used Production Data

26. Creating Data Flow Diagrams Level 1 DFD Example Create a level 1 decomposing the processes in level 0 and identifying data stores. 4.Construct Level 1 (continued) Customer Order Serve Product Collect Payment Produce Product Store Product Order Raw Materials Pay for Raw Materials Pay for Labor 3.1 Produce Purchase Order Order Decision PURCHASE ORDER 3.2 Receive Items Received Goods RAW MATERIALS 3.3 Pay Vendor Quantity Received Quantity On-Hand RECEIVED ITEMS VENDOR Payment Approval Payment

27. Creating Data Flow Diagrams Level 1 DFD Example Create a level 1 decomposing the processes in level 0 and identifying data stores. 4.Construct Level 1 (continued) Time Worked Customer Order Serve Product Collect Payment Produce Product Store Product Order Raw Materials Pay for Raw Materials Pay for Labor 4.1 Record Time Worked TIME CARDS 4.2 Calculate Payroll Payroll Request EMPLOYEE 4.3 Pay Employe e Employee ID PAYROLL PAYMENTS Payment Approval Payment Unpaid time cards

28. Process Decomposition 4.1 Record Time Worked 4.2 Calculate Payroll 4.3 Pay Employe e 3.1 Produce Purchase Order 3.2 Receive Items 3.3 Pay Vendor 2.1 Serve Product 2.2 Produce Product 2.3 Store Product 1.1 Record Order 1.2 Receive Payment 2.0 Production 1.0 Sale 3.0 Procure- ment 4.0 Payroll 0.0 Lemonade System Level 0Level 1Context Level

29. DFD Example: Bus Garage Repairs  Buses come to a garage for repairs.  A mechanic and helper perform the repair, record the reason for the repair and record the total cost of all parts used on a Shop Repair Order.  Information on labor, parts and repair outcome is used for billing by the Accounting Department, parts monitoring by the inventory management computer system and a performance review by the supervisor.

30. DFD Example: Bus Garage Repairs (cont’d)  External Entities: Bus, Mechanic, Helper, Supervisor, Inventory Management System, Accounting Department, etc.  Key process (“the system”): performing repairs and storing information related to repairs  Processes:  Record Bus ID and reason for repair  Determine parts needed  Perform repair  Calculate parts extended and total cost  Record labor hours, cost

31. DFD Example: Bus Garage Repairs (cont’d)  Data stores:  Personnel file  Repairs file  Bus master list  Parts list  Data flows:  Repair order  Bus record  Parts record  Employee timecard  Invoices

32. Bus Mechanic Helper Bus Repair Process System Supervisor Accountin g Bus Garage Context Diagram Mechanical problem to be repaired Labor Fixed mechanical problems Inventory Managemen t System Repair summary List of parts used Labor, parts cost details

33. CSUB Burger’s Order Processing System  Draw the CSUB Burger’s context diagram  System Order processing system  External entities Kitchen Restaurant Customer  Processes Customer order Receipt Food order Management report Example Ref by Yong Choi BPA CSUB

34. Insulin pump DFD

35. Event-driven Modeling (State machine models)  These model the behaviour of the system in response to external and internal events.  They show the system’s responses to stimuli so are often used for modelling real-time systems.  State machine models show system states as nodes and events as arcs between these nodes. When an event occurs, the system moves from one state to another.  State charts are an integral part of the UML and are used to represent state machine models.

36. Statecharts  Allow the decomposition of a model into sub-models (see following slide).  In UML, state diagrams rounded rectangles represent system states.  A brief description of the actions is included following the ‘do’ in each state.  The labeled arrows represent stimuli that force action from one state to another  Start & end state are represented by filled circle.

37. Microwave oven model

38. Microwave oven state description

39. Microwave oven stimuli

40. Microwave oven operation

41. Semantic (Structural) data models  Used to describe the logical structure of data processed by the system.  An entity-relation-attribute model sets out the entities in the system, the relationships between these entities and the entity attributes  Widely used in database design. Can readily be implemented using relational databases.  No specific notation provided in the UML but objects and associations can be used.

42. Library semantic model

43. Data dictionaries  Data dictionaries are lists of all of the names used in the system models. Descriptions of the entities, relationships and attributes are also included.  Advantages  Support name management and avoid duplication;  Store of organisational knowledge linking analysis, design and implementation;  Many CASE workbenches support data dictionaries.

44. Data dictionary entries

45. Object models  Object models describe the system in terms of object classes and their associations.  An object class is an abstraction over a set of objects with common attributes and the services (operations) provided by each object.  Various object models may be produced  Inheritance models;  Aggregation models;  Interaction models.

46. Object models  Natural ways of reflecting the real-world entities manipulated by the system  More abstract entities are more difficult to model using this approach  Object class identification is recognised as a difficult process requiring a deep understanding of the application domain

47. Inheritance models  Organise the domain object classes into a hierarchy.  Classes at the top of the hierarchy reflect the common features of all classes.  Object classes inherit their attributes and services from one or more super-classes. these may then be specialised as necessary.  Class hierarchy design can be a difficult process if duplication in different branches is to be avoided.

48. Object models and the UML  The UML is a standard representation devised by the developers of widely used object-oriented analysis and design methods.  It has become an effective standard for object-oriented modelling.  Notation  Object classes are rectangles with the name at the top, attributes in the middle section and operations in the bottom section;  Relationships between object classes (known as associations) are shown as lines linking objects;  Inheritance is referred to as generalisation and is shown ‘upwards’ rather than ‘downwards’ in a hierarchy.

49. Library class hierarchy

50. User class hierarchy

51. Multiple inheritance  Rather than inheriting the attributes and services from a single parent class, a system which supports multiple inheritance allows object classes to inherit from several super-classes.  This can lead to semantic conflicts where attributes/services with the same name in different super-classes have different semantics.  Multiple inheritance makes class hierarchy reorganisation more complex.

52. Multiple inheritance

53. Object aggregation  An aggregation model shows how classes that are collections are composed of other classes.  Aggregation models are similar to the part-of relationship in semantic data models.

54. Object aggregation

55. Object behaviour modelling  A behavioural model shows the interactions between objects to produce some particular system behaviour that is specified as a use-case.  Sequence diagrams (or collaboration diagrams) in the UML are used to model interaction between objects.

56. Issue of electronic items

57. Sequence Diagram  Objects & actors are listed along top of the diagram with a dotted line drawn vertically  The rectangle on dotted line indicated the lifeline of the object  Read the sequence of interaction from top to bottom  The annotation on arrow show the calls to the objects, their parameter & return value  Alternatives is used for conditions in square bracket

58. View Patient Information

59. Order processing

60. Sequence diagram describing data collection

61. CASE workbenches  A coherent set of tools that is designed to support related software process activities such as analysis, design or testing.  Analysis and design workbenches support system modelling during both requirements engineering and system design.  These workbenches may support a specific design method or may provide support for a creating several different types of system model.

62. An analysis and design workbench

63. Analysis workbench components  Diagram editors  Model analysis and checking tools  Repository and associated query language  Data dictionary  Report definition and generation tools  Forms definition tools  Import/export translators  Code generation tools

64. Model-driven engineering  Model-driven engineering (MDE) is an approach to software development where models rather than programs are the principal outputs of the development process.  The programs that execute on a hardware/software platform are then generated automatically from the models.  Proponents of MDE argue that this raises the level of abstraction in software engineering so that engineers no longer have to be concerned with programming language details or the specifics of execution platforms. Chapter 5 System modeling 64

65. Usage of model-driven engineering  Model-driven engineering is still at an early stage of development, and it is unclear whether or not it will have a significant effect on software engineering practice.  Pros  Allows systems to be considered at higher levels of abstraction  Generating code automatically means that it is cheaper to adapt systems to new platforms.  Cons  Models for abstraction and not necessarily right for implementation.  Savings from generating code may be outweighed by the costs of developing translators for new platforms. 65

66. Model driven architecture  Model-driven architecture (MDA) was the precursor of more general model-driven engineering  MDA is a model-focused approach to software design and implementation that uses a subset of UML models to describe a system.  Models at different levels of abstraction are created. From a high-level, platform independent model, it is possible, in principle, to generate a working program without manual intervention. Chapter 5 System modeling 66

67. Types of model  A computation independent model (CIM)  These model the important domain abstractions used in a system. CIMs are sometimes called domain models.  A platform independent model (PIM)  These model the operation of the system without reference to its implementation. The PIM is usually described using UML models that show the static system structure and how it responds to external and internal events.  Platform specific models (PSM)  These are transformations of the platform-independent model with a separate PSM for each application platform. In principle, there may be layers of PSM, with each layer adding some platform- specific detail. Chapter 5 System modeling 67

68. MDA transformations 68 Chapter 5 System modeling

69. Multiple platform-specific models 69 Chapter 5 System modeling

70. Agile methods and MDA  The developers of MDA claim that it is intended to support an iterative approach to development and so can be used within agile methods.  The notion of extensive up-front modeling contradicts the fundamental ideas in the agile manifesto and I suspect that few agile developers feel comfortable with model-driven engineering. Chapter 5 System modeling 70

71. Executable UML  The fundamental notion behind model-driven engineering is that completely automated transformation of models to code should be possible.  This is possible using a subset of UML 2, called Executable UML or xUML. Chapter 5 System modeling 71

72. Features of executable UML  To create an executable subset of UML, the number of model types has therefore been dramatically reduced to these 3 key types:  Domain models that identify the principal concerns in a system. They are defined using UML class diagrams and include objects, attributes and associations.  Class models in which classes are defined, along with their attributes and operations.  State models in which a state diagram is associated with each class and is used to describe the life cycle of the class. 72

73. Key points  Behavioral models are used to describe the dynamic behavior of an executing system. This behavior can be modeled from the perspective of the data processed by the system, or by the events that stimulate responses from a system.  Activity diagrams may be used to model the processing of data, where each activity represents one process step.  State diagrams are used to model a system’s behavior in response to internal or external events.  Model-driven engineering is an approach to software development in which a system is represented as a set of models that can be automatically transformed to executable code. Chapter 5 System modeling 73