1. DESIGN

2. Quick Summary What you have learnt so far?
Different kinds of software engineering methodology
Waterfall model
Spiral model
Unified process
Requirements :Use cases
Traditional specification: semi-formal
DFD
Formal specification: Z, FSM, Petric Nets
Object-oriented specification
Class extraction, various diagram to present the class relationships

3. Design with formal specification
Example give a Z specification
Can you write program codes for a “push_button” ?

4. Data and Actions Two aspects of a product Actions that operate on data
Data on which actions operate
The two basic ways of designing a product
Operation-oriented design
Data-oriented design
Third way
Hybrid methods
For example, object-oriented design that combines features of operation-oriented design and data-oriented design
Recall the Data Flow Diagram (DFD), how can you design a software based on a DFD?
Object-oriented design is a combination of both operation-oriented and data-oriented

5. 13.1 Design and Abstraction
Classical design activities
Architectural design – general and high-level
Detailed design
Design testing
Architectural design – create modules of the software
Input: Specifications document
Output: Modular decomposition of the software
Each module is designed
Specific algorithms and data structures are selected
If OOP is used then architectural design is not required, why?
Because “classes” already derived during specification
Detailed design – specific algorithms are selected and data structures are chosen

6. 13.2 Operation-Oriented Design
If system can be presented in a DFD
Data flow analysis (DFA)
Can use DFA with most specification methods (Structured Systems Analysis is presented here)
Key point: We have detailed action information from the DFD (ie input to and output from the product)
Figure 13.1

7. Data Flow Analysis Every product transforms input into output
Determine
“Point of highest abstraction of input”
“Point of highest abstract of output”
Point of highest abstraction of input – point at which the input loses the quality of being input and simply becomes internal data
operated by the product
Point of highest abstraction of output – point at which data can be identified as some form of output
Figure 13.2

8. Data flow analysis
Point of highest abstraction of input – point at which the input loses the quality of being input and simply becomes internal data operated by the product
Example – input is a membership number the output could be a flag (valid/ not valid) and a discount %
Point of highest abstraction of output – point at which data can be identified as some form of output
Example – an array collecting all information ready to print out

9. Example A software to solve circuit related problems
Input: V, I, R, Z etc
At point of highest abstraction: a matrix
Output: the unknown V at t = 10ms
Other examples based on your own experiences?

10. Data Flow Analysis (contd)
Decompose the product into three modules
Input, transform, and output
Repeat stepwise until each module performs a single operation: high cohesion
Minor modifications may be needed to lower the coupling
Cohesion – degree of interaction within a module
Coupling – degree of interaction between modules
Cohesion - 結合;凝聚;團結力;附著

11. Cohesion The degree of interaction within a module
Seven categories or levels of cohesion (non-linear scale)
Figure 7.4

12. Coincidental Cohesion
A module has coincidental cohesion if it performs multiple, completely unrelated actions
Example modules:
print_next_line, reverse_string_of_characters_comprising_second_parameter, add_7_to_fifth_parameter, convert_fourth_parameter_to_ floating_point
Such modules arise from rules like
“Every module will consist of between 35 and 50 statements” so unrelated functions put together in order to fit the size!

13. Why Is Coincidental Cohesion So Bad?
It degrades maintainability – too many things to consider
A module with coincidental cohesion is not reusable – as it is doing too many things which are difficult to find other programs using all the same features
The problem is easy to fix
Break the module into separate modules, each performing one task

14. Logical Cohesion
A module has logical cohesion when it performs a series of related actions, one of which is selected by the calling module

15. Logical Cohesion (contd)
Example 1:
function_code = 7;
new_operation (op code, dummy_1, dummy_2, dummy_3);
// dummy_1, dummy_2, and dummy_3 are dummy variables,
// not used if function code is equal to 7
Example 2:
An object performing all input and output
Example 3:
A module that edits insertions, deletions, and modifications of master file records

16. Why Is Logical Cohesion So Bad?
The interface is difficult to understand as there may be many irrelevant information (such as dummy variables)
Code for more than one action may be intertwined
Difficult to reuse

17. Why Is Logical Cohesion So Bad? (contd)
A new tape unit is installed then the new codes will be added that may be inter-twined with the part related to another printer such as section numbered 1,2,3,4,6,9,10
Figure 7.5

18. Temporal Cohesion
A module has temporal cohesion when it performs a series of actions related in time
Example:
open_old_master_file, new_master_file, transaction_file, and print_file; initialize_sales_district_table, read_first_transaction_record, read_first_old_master_record (a.k.a. perform_initialization)

19. Why Is Temporal Cohesion So Bad?
The actions of this module are weakly related to one another, but strongly related to actions in other modules
Consider sales_district_table is being initialized in that module but changing the table is via a different module
When changing a data it will involve many modules some of which may be overlooked
Not reusable – same reason no other software will need all the functions

20. Procedural Cohesion
A module has procedural cohesion if it performs a series of actions related by the procedure to be followed by the product
Example:
read_part_number_and_update_repair_record_on_ master_file

21. Why Is Procedural Cohesion So Bad?
The actions are still weakly connected, so the module is not reusable

22. Communicational Cohesion
A module has communicational cohesion if it performs a series of actions related by the procedure to be followed by the product, but in addition all the actions operate on the same data
Example 1:
update_record_in_database_and_write_it_to_audit_trail
Both working with record
Example 2:
calculate_new_coordinates_and_send_them_to_terminal
Both working with coordinates

23. Why Is Communicational Cohesion So Bad?
Still lack of reusability

24. Functional Cohesion
A module with functional cohesion performs exactly one action

25. 7.2.6 Functional Cohesion Example 1: Example 2: Example 3: Example 4:
get_temperature_of_furnace
Example 2:
compute_orbital_of_electron
Example 3:
write_to_diskette
Example 4:
calculate_sales_commission

26. Why Is Functional Cohesion So Good?
More reusable
Common functions can be reused easily
Corrective maintenance is easier
Fault isolation – easy to focus
Fewer regression faults
Easier to extend a product – add more functions

27. Informational Cohesion
A module has informational cohesion if it performs a number of actions, each with its own entry point, with independent code for each action, all performed on the same data structure

28. Why Is Informational Cohesion So Good?
Essentially, this is an abstract data type (see later)

29. Cohesion Example
Figure 7.7

30. Example
When two or more different levels of cohesion can be assigned to a module is to assign the lowest possible level

31. Coupling The degree of interaction between two modules
Five categories or levels of coupling (non-linear scale)
Figure 7.8

32. Content Coupling
Two modules are content coupled if one directly references contents of the other
Example 1:
Module p modifies a statement of module q
Example 2:
Module p refers to local data of module q in terms of some numerical displacement within q
Example 3:
Module p branches into a local label of module q
Not so common in writing high level language programming

33. Why Is Content Coupling So Bad?
Almost any change to module q, even recompiling q with a new compiler or assembler, requires a change to module p
Difficult to reuse only module p

34. Common Coupling
Two modules are common coupled if they have write access to global data
Example 1
Modules cca and ccb can access and change the value of global_variable
Figure 7.9

35. Common Coupling Example 2:
Modules cca and ccb both have access to the same database, and can both read and write the same record
Example 3:
FORTRAN common
COBOL common (nonstandard)
COBOL-80 global

36. Why Is Common Coupling So Bad?
It contradicts the spirit of structured programming
The resulting code is virtually unreadable
What causes this loop to terminate if global_variable is a global variable
As its value can be changed with many possibilities
Figure 7.10

37. Why Is Common Coupling So Bad? (contd)
Modules can have side-effects
This affects their readability
Example: edit_this_transaction (record_7)
The entire module source must be read to find out what it does because other global variables (not just record_7) may be changed by the function
A change during maintenance to the declaration of a global variable in one module necessitates corresponding changes in other modules
Common-coupled modules are difficult to reuse because global variables are missing in the new software system

38. Why Is Common Coupling So Bad? (contd)
Common coupling between a module p and the rest of the product can change without changing p in any way
For example, if both module p and q can modify global variable gv then there is one instance of common coupling between p and the other modules. But if 10 new modules are designed and implemented, all of which can modify global variable gv, then the number of instances of common coupling between module p and the other modules increases to 11
A module is exposed to more data than necessary
This can lead to computer crime as control of data access is reduced

39. Control Coupling
Two modules are control coupled if one passes an element of control to the other
Example 1:
An operation code is passed to a module with logical cohesion
Example 2:
A control switch passed as an argument

40. Control Coupling (contd)
Module p calls module q
Message:
I have failed (a flag) — data
I have failed, so write error message ABC123 — control
The return by q is controlling the action of p (ie to display the corresponding error message)

41. Why Is Control Coupling So Bad?
The modules are not independent
Module q (the called module) must know the internal structure and logic of module p otherwise cannot pass back the proper control
This affects reusability
Modules are usually logical cohesion

42. Stamp Coupling
Some languages allow only simple variables as parameters
part_number
satellite_altitude
degree_of_multiprogramming
Many languages also support the passing of data structures
part_record
satellite_coordinates
segment_table

43. Stamp Coupling (contd)
Two modules are stamp coupled if a data structure is passed as a parameter, but the called module operates on some but not all of the individual components of the data structure

44. Why Is Stamp Coupling So Bad?
It is not clear, without reading the entire module, which fields of a record (employee_record) are accessed or changed
Example
calculate_withholding (employee_record)
Difficult to understand
Unlikely to be reusable
More data than necessary is passed
Uncontrolled data access can lead to computer crime

45. Why Is Stamp Coupling So Bad? (contd)
However, there is nothing wrong with passing a data structure as a parameter, provided that all the components of the data structure are accessed and/or changed
Examples:
invert_matrix (original_matrix, inverted_matrix);
print_inventory_record (warehouse_record);

46. Data Coupling
Two modules are data coupled if all parameters are homogeneous data items (simple parameters, or data structures all of whose elements are used by called module)
Examples:
display_time_of_arrival (flight_number);
compute_product (first_number, second_number);
get_job_with_highest_priority (job_queue);

47. Why Is Data Coupling So Good?
The difficulties of content, common, control, and stamp coupling are not present
Maintenance is easier because a change in one module is less likely to cause a regression fault in the other

48. Coupling Example The number in the link is the interface
P calls q with interface (1)
Figure 7.11

49. Coupling Example (contd)
Figure 7.12
Interface description

50. Coupling Example (contd)
Figure 7.13
Coupling between all pairs of modules

51. Mini Case Study: Word Counting
Example:
Design a product which takes as input a file name, and returns the number of words in that file (like UNIX wc )
Figure 13.3
From programming point of view
A file pointer is used to present the file

52. Mini Case Study: Word Counting (contd)
First refinement – represented using structured diagram
Now refine the two modules of communicational cohesion
Read_and_validate_file_name
shows a communicational cohesion
it performs a series of operations
related by the sequence of steps
In the structured diagram (SD), each node represent a module.
A module is a functional abstraction to be implemented by a software module
Usually assume a modules are called by a master module (transaction flow centered)
SD is derived from the DFD
Communication cohesion – a series of operations related by the sequence of steps to be followed by the product and if all the operations are performed on the same data

53. Structure diagram
In the structured diagram (SD), each node represent a module.
A module is a functional abstraction to be implemented by a software module
Usually assume a modules are called by a master module (transaction flow centered)
SD is derived from the DFD

54. Mini Case Study: Word Counting (contd)
Second refinement
All eight modules now have functional cohesion
Functional cohesion – a module that performs exactly one operation or achieves a single goal
Figure 13.5

55. Word Counting: Detailed Design
The architectural design is complete
So proceed to the detailed design
Data structures are chosen
Algorithms selected
The detailed design is handed to a programmer for implementation
Two formats for representing the detailed design:
Tabular
Pseudocode (PDL — program design language)
PDL is usually used if the programming language is chosen

56. Detailed Design: Tabular Format
Figure 13.6(a)

57. Detailed Design: Tabular Format (contd)
Figure 13.6(b)

58. Detailed Design: Tabular Format (contd)
Figure 13.6(c)

59. Detailed Design: Tabular Format (contd)
Figure 13.6(d)

60. Detailed Design: PDL Format
The structure of the above PDL is similar to the C/C++ or Java languages
Converting the comments into program codes then the program is done
Figure 13.7

61. 13.3.2 Data Flow Analysis Extensions
In real-world products, there is
More than one input stream, and
More than one output stream

62. Data Flow Analysis Extensions
Find the point of highest abstraction for each stream
Continue until each module has high cohesion
Adjust the coupling if needed
Figure 13.8

63. Exercise
Based on the DFD of the library system, design the circulation system using data flow analysis
Draw the structured diagram (2 iterations)
Detailed design of “obtained_catalog_information”
PDL for “check_out_book”

64. Exercise
Convert the above Z specification into a PDL

65. Data-Oriented Design Basic principle
Design the product according to the structure of the data on which it is to operate
Each procedure is given the same structure as the data on which it operates
Three very similar methods
Michael Jackson [1975], Warnier [1976], Orr [1981]
Data-oriented design
Has never been as popular as action-oriented design
With the rise of OOD, data-oriented design has largely fallen out of fashion
Not very popular

66. 13.6 Object-Oriented Design (OOD)
Aim
Design the product in terms of the classes extracted during OOA
If we are using a language without inheritance (e.g., C, Ada 83)
Use abstract data type design
If we are using a language without a type statement (e.g., FORTRAN, COBOL)
Use data encapsulation
OOD – can be adopted by other non-OOP languages
Abstract data type and data encapsulation are two major features of OOD

67. Object-Oriented Design Steps
OOD consists of two steps:
Step 1. Complete the class diagram
Determine the formats of the attributes
Assign each method, either to a class or to a client that sends a message to an object of that class
Step 2. Perform the detailed design

68. Object-Oriented Design Steps (contd)
Step 1. Complete the class diagram
The formats of the attributes can be directly deduced from the analysis artifacts
Example of deriving an attribute: Dates
U.S. format (mm/mm/yyyy)
European format (dd/mm/yyyy)
In both instances, 10 characters are needed

69. Object-Oriented Design Steps (contd)
Step 1. Complete the class diagram
Assign each method, either to a class or to a client that sends a message to an object of that class
Principle A: Information hiding
Principle B: If an operation is invoked by many clients of an object, assign the method to the object, not the clients
Principle C: Responsibility-driven design (class receiving the request is responsible to carry out the operation)
Information hiding – a class can have state variables declared as private or protected.
Operations performed on state variables must be local to that class (information of the variable is hidden from the outside)

70. Information hiding
An object is a collection of data and function so entities outside an object does not know what is inside (information is hidden from the outside world!!!)

71. 13.7 Object-Oriented Design: The Elevator Problem Case Study
Step 1. Complete the class diagram
Need to identify methods (functions) of a class
Consider the second iteration of the CRC card for the elevator controller

72. OOD: Elevator Problem Case Study
CRC card
Figure 12.9 (again)

73. OOD: Elevator Problem Case Study (contd)
Responsibilities
8. Start timer
10. Check requests, and
11. Update requests
are assigned to the elevator controller
Because they are carried out by the elevator controller – according to responsibility-driven design

74. OOD: Elevator Problem Case Study (contd)
The remaining eight responsibilities have the form
“Send a message to another class to tell it do something”
These should be assigned to that other class
Responsibility-driven design
Safety considerations
Methods open doors, close doors are assigned to class Elevator Doors Class
Methods turn off button, turn on button are assigned to classes Floor Button Class and Elevator Problem Class

75. Detailed Class Diagram: Elevator Problem
Figure 13.11

76. Detailed Design: Elevator Problem
Detailed design of elevatorEventLoop is constructed from the statechart
Figure 13.12

77. Dynamic Modeling: The Elevator Problem Case Study
Produce a UML statechart
State, event, and predicate are distributed over the statechart
Aim of dynamic modeling is to produce the state chart
State chart provides a description of the target product similar to a finite state machine for each class
The above is the state chart for the elevator controller class only!!
Elevator event loop, going into wait state etc are states
Elevator stopped no requests pending – event
Close elevator doors after timeout – operation to be carried out when the state “Going into wait state” has been entered
Figure 12.7

78. 13.8 Object-Oriented Design: The MSG Foundation Case Study
Step 1. Complete the class diagram
The final class diagram is shown in the next slide
Date Class is needed for C++
Java has built-it functions for handling dates

79. Final Class Diagram: MSG Foundation
Figure 13.13

80. Class Diagram with Attributes: MSG Foundation
Figure 13.14

81. Assigning Methods to Classes: MSG Foundation
Example: setAssetNumber, getAssetNumber
From the inheritance tree, these accessor/mutator methods should be assigned to Asset Class
So that they can be inherited by both subclasses of Asset Class (Investment Class and Mortgage Class)
Accessor – function to obtain attribute of a class
Mutator – function that modify attribute of a class
Figure 13.15

82. Assigning Methods to Classes: MSG Foundation

83. Detailed Design: MSG Foundation
Determine what each method does
Represent the detailed design in an appropriate format
PDL (pseudocode) here

84. Method EstimateFundsForWeek::computeEstimatedFunds
Figure 13.16

85. Method Mortgage::totalWeeklyNetPayments
Figure 13.17

86. 13.9 The Design Workflow Summary of the design workflow:
The analysis workflow documents (input for design workflow) are iterated and integrated until the programmers can utilize them
Major tasks to achieve – identify the methods to be assigned to classes as well as performing detailed design
Decisions to be made include:
What programming language to use
Reuse of existing software components
Portability – work under different software/hardware platform

87. The Design Workflow (contd)
The idea of decomposing a large workflow into independent smaller workflows (packages) is carried forward to the design workflow
The objective is to break up the upcoming implementation workflow into manageable pieces
Subsystems
It does not make sense to break up the MSG Foundation case study into subsystems — it is too small
Package – a term used in C++ or other OOP languages to describe a concept similar to a library

88. The Design Workflow (contd)
Why the product is broken into subsystems:
It is easier to implement a number of smaller subsystems than one large system
If the subsystems are independent, they can be implemented by programming teams working in parallel
The software product as a whole can then be delivered sooner

89. The Design Workflow (contd)
The architecture of a software product includes
The various components
How they fit together
The allocation of components to subsystems
The task of designing the architecture is specialized
It is performed by a software architect

90. The Design Workflow (contd)
The architect needs to make trade-offs
Every software product must satisfy its functional requirements (the use cases)
It also must satisfy its nonfunctional requirements, including
Portability, reliability, robustness, maintainability, and security
It must do all these things within budget and time constraints
The architect must assist the client by laying out the trade-offs – balance between the requirements and the budget

91. The Design Workflow (contd)
It is usually impossible to satisfy all the requirements, functional and nonfunctional, within the cost and time constraints
Some sort of compromises have to be made
The client has to
Relax some of the requirements;
Increase the budget; and/or
Move the delivery deadline
The software architect must provide expert knowledge to assist the client to make the proper decision !!!!

92. The Design Workflow (contd)
The architecture of a software product is critical
The requirements workflow can be fixed during the analysis workflow
The analysis workflow can be fixed during the design workflow
The design workflow can be fixed during the implementation workflow
But there is no way to recover from a suboptimal architecture
The architecture must immediately be redesigned

93. 13.10 The Test Workflow: Design
Testing the design
Design reviews (testing) must be performed
The design must correctly reflect the specifications
The design itself must be correct

94. 13.11 The Test Workflow: The MSG Foundation Case Study
A design inspection must be performed
All aspects of the design must be checked
Even if no faults are found, the design may be changed during the implementation workflow

95. 13.12 Formal Techniques for Detailed Design
Implementing a complete product and then proving it correct is hard
However, use of formal techniques during detailed design can help
Correctness proving can be applied to module-sized pieces
The design should have fewer faults if it is developed in parallel with a correctness proof
If the same programmer does the detailed design and implementation
The programmer will have a positive attitude to the detailed design
This should lead to fewer faults
Assume developing the proof and the detailed design in parallel

96. 13.15 Metrics for Design Measures of design quality Cohesion Coupling
Fault statistics
Cyclomatic complexity (M) – counting the number of binary decisions (branches) plus 1; the lower the value of M, the better
CC = 1 if no decision is made
Cyclomatic complexity is problematic
Data complexity is ignored (the value M is related to the control complexity)
It is not used much with the object-oriented paradigm

97. Cyclomatic Complexity
What is the cyclomatic
complexity for the
flow graph?

98. Metrics for Design (contd)
Metrics have been put forward for the object-oriented paradigm
They have been challenged on both theoretical and experimental grounds
There is no suitable metric for OOD

99. 13.16 Challenges of the Design Phase
The design team should not do too much
The detailed design should not become code
The design team should not do too little
It is essential for the design team to produce a complete detailed design