Function oriented design

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1. Function-Oriented Design
Module 3
Sangeetha Jose
Lecturer in IT,
Govt. Engg. College
Idukki

2. Design
A process to design (verb)
Result of the design process (noun)

3. Different levels…
System design or top-level design (modular level)
Detailed design (Internal design of the module)

4. Design methodology
….is a systematic approach to create a design by
applying of a set of techniques and guidelines
Input – specifications of the system to be designed
Output – system design

5. Object Oriented Design
vs
Function Oriented Design
Object - oriented : modules in the design represent data
abstraction
Function - oriented : consists of module definitions, with each
module supporting a functional abstraction
Function-oriented design views a system as a set of modules
with clearly defined behavior that interact with each other in a
clearly defined manner to meet the system's requirements.

6. Design Objectives
The goal of software design is to find the best
possible design that meets your needs
You may have to explore different designs
Unfortunately, evaluation criteria for a design
are often subjective and non-quantifiable

7. Major criteria to evaluate a design

Correctness
•A software design is correct if a system built precisely according to
the requirements of the system
•A design should be verifiable (does an implementation match the
design), complete (does the design address its specified
requirements) and traceable (all design elements can be traced
back to specific requirements)
Efficiency
•Does the design efficiently make use of scarce resources: such as
memory on a wireless sensor
Maintainability and Simplicity
•How easy is it for the design of a system to be understood?
•Simpler designs make it easy for a developer to understand and
then maintain the system
Cost
•Does the design help to reduce costs in later phases of software
development?
•Can one design achieve the same quality as another design while
reducing costs?

8. Problem analysis Vs Design Principles
Constructing a model of
problem domain
Model depends on the
system
Model is used to
understand the problem
Constructing a model of
solution domain
System depends on the
model
Model is used for
optimization

9. Design Principles
Problem Partitioning and Hierarchy
Abstraction
Modularity
Top-Down and Bottom-Up Strategies

10. Problem Partitioning and Hierarchy
Divide and Conquer
Decompose system into smaller and smaller pieces
Ideally, each piece can be solved separately
Ideally, each piece can be modified independent of other pieces
Reality: each piece must communicate with other pieces
This communication implies a certain cost
At some point the cost is more than the benefit provided by the
individual pieces
At this point, the decomposition process can stop

11. Abstraction
Abstraction is a powerful concept used in all
engineering disciplines

It is a tool that permits a developer to consider a
component in terms of the services (behaviors) it
provides without worrying about the details of its
implementation

12. Contd…
Abstraction is an excellent tool for creating a hierarchical
understanding of a system's functionality
In design contexts, you might see references to two “types” of
abstraction
functional abstraction: a module is specified by the functions it
performs
data abstraction: a data structure is manipulated in terms of pre-
defined operations; the implementation of the data structure is
hidden from its users (only operations are visible)
The former is primarily used in functional design, the latter is used
primarily in object-oriented design

13. Modularity
A system is considered modular if it consists of discreet
components so that each component can be
implemented separately, and a change to one
component has minimal impact on other components
Helps in system repair and in system building
Each component needs to support a well-defined
abstraction and have a specific interface that other
modules use to interact with it
As Jalote says “Modularity is where abstraction and
partitioning come together”.

14. Top-Down vs Bottom-Up Design
A system consists of a set of components, which have
subcomponents of their own
The highest level component is the system itself, a concept we
have seen when discussing context diagrams
We can design such a hierarchy using either a top-down
approach or a bottom-up approach
In reality, we use both approaches and meet in the middle
A top-down approach starts with the system as a whole, and
using stepwise refinement, decomposes it into sub-
components that exist at lower levels of abstraction

15. Contd…
A bottom-up approach starts with primitive components that
provide foundational services and using layers of abstraction
builds the functionality the system needs until the entire system
has been realized
A top-down approach is typically more useful in situations only if
the specifications of the system are clearly known and
application is being built from scratch (water fall model)
A bottom-up approach is thus more useful in situations in which
a new application is being created from an existing (legacy)
system (Iterative enhancement model)

16. Module
It is a logically separable part of a program
It is a program unit that is discreet and identifiable with
respect to compiling and loading
Can be a function, a procedure, a process or a package

17. Module-Level Concepts
Coupling
Cohesion

18. Coupling
“how strongly” different modules are interconnected
By definition,
“Coupling between modules is the strength of interconnections
between modules or a measure of interdependence among modules”
An abstract concept and is not easily quantifiable
Highly coupled – strong interconnections
loosely coupled – weak interconnections

19. Contd…
Factors influencing coupling are :
type of connection between modules
the complexity of the interface
the type of information flow between modules
Minimize the number of interfaces per module and the
complexity of each interface
Depends up on the type of information flow, coupling varies
Data Flow – Minimal
Hybrid – Maximum (data and control)

20. Factors affecting coupling

21. Cohesion
Cohesion is the concept that tries to capture intra-module bonds
Shows how closely the elements of a module are related to each
other.
Shows how tightly bound the internal elements of the module are to
one another
Usually, greater the cohesion of each module in the system, the
lower the coupling between module is.
cohesion: how focused is an object (or module, or function, or
package, etc.) on a particular task or concern
a highly cohesive object has attributes and behavior that relate
only to one task or concern

22. Levels of cohesion
Coincidental Low
Logical
Temporal
Procedural
Communicational
Sequential
Functional High

23. Details…
Coincidental Cohesion occurs when there is no meaningful
relationship among the elements of a module.
Logical Cohesion: if there is some logical relationship between
the elements of a module (input and output modules)
Temporal cohesion: same as logical cohesion, except that the
elements are also related in time and are executed together
(initialization, clean-up, termination)
Procedurally cohesive module contains elements that belong
to a common procedural unit (loop or a sequence of decision
statements)

24. Contd…
Communicational cohesion has elements that are related
by a reference to the same input or output data (may
perform more than one function)
Sequential cohesion occurs when output of one forms the
input to another.
In functional cohesion all the elements of the module are
related to performing a single function (single function or
single goal – “compute square root” or “sort the array”)

25. How does one determine the cohesion
level of a module?
Compound sentence : sequential or communicational
cohesion
“first”, “next”, “when”, “after” : sequential or temporal
“edit all data” : logical cohesion
“initialize” or “cleanup” : temporal cohesion

26. We aim to create systems out of highly cohesive,
loosely coupled components…

27. Design Notations
Structure charts
UML

28. Structure Charts
A structure chart is a graphical representation of a system's structure;
in particular, its modules and their interconnections
Each module is represented by a box
If A uses B, then an arrow is drawn from A to B
B is called the subordinate of A
A is called the superordinate of B

An arrow is labeled with the parameters received by B as input and
the parameters returned by B as output
Arrows indicate the direction in which parameters flow
Parameters can be data (shown as unfilled circles at the tail of a
label) or control information (filled circles at the tail)

29. The structure chart of the sort program

30. Supports Iteration and Branching

31. Types of Modules
Input: A module that only produces information that is
passed to its superordinate
Output: A module that only receives information from
its superordinate for output to a device
Transform: A module that converts data from one
format into another format, possibly generating entirely
new information.
Coordinator: A module that manages the flow of data
to and from different subordinates
Composite: Modules that combine one or more of the
above styles are composite modules

32. Different types…

33. Design specification
A designer must also create a textual specification for
each module that appears in the system's structure
Design specification contains
1. Problem Specification
2. Major Data Structures
3. Modules and their Specifications
4. Design Decisions

34. Structured Design Methodology
The structured design methodology (SDM)
views a system as a transformation function that
transforms specified inputs into specified outputs.

35. Factoring
A key concept of SDM is factoring
Factoring is the process of decomposing a
module so that the bulk of its work is done by its
subordinates
SDM attempts to achieve a structure that is
close to being completely factored

36. SDM Strategy
The overall strategy of SDM is to identify the input and output streams of
the system and the primary transformations that have to be performed to
produce the output
High-level modules are then created to perform these major activities,
which are later refined (factored)
There are four major steps in applying this strategy
Restate the problem as a data flow diagram
Identify the input and output data elements
Perform first-level factoring
Perform additional factoring on input, output and transform branches
created in the previous step

37. Step 1: Restate the problem as a
data flow diagram
DFD represents how the data will flow in the system
when it is built.
Data flow diagrams during design are focused on the
solution domain
What are the inputs and outputs of our system (as
opposed to the inputs and outputs of the problem
domain)?
What are the central transformations?

38. Example 1: DFD for an ATM
Back

39. Example 2: DFD for a word-counting
program
Back

40. Step 2: Identify the input and
output data elements
What we are looking for is the most abstract input elements (MAI)
and the most abstract output elements (MAO)
The MAI elements are found by going as far as possible from
physical inputs without losing the incoming nature of the data
element
The MAO elements are found by identifying the data elements
most removed from the physical outputs without losing the
outgoing nature of the data element
Figure1 Figure2

41. Step 3: First-Level Factoring
First-level factoring is the first step towards converting the DFD into
a structure chart
You start by creating a module that represents the software system
(the main module)
The main module acts as a coordinator module
For each MAI data element, specify a subordinate input module that
delivers these items to the main module
For each MAO data element, specify an output module
For each central transform, specify a subordinate transform module
The inputs and outputs of these transform modules are specified in
the DFD

42. Example 1: First-Level Factoring of
word-counting example

43. Example 2: First-Level Factoring of ATM
example

44. Step 4: Perform Additional Factoring
Now stepwise refinement is used to specify the sub-
modules required to realize the functionality of the
modules created in the previous step
For each input module:
assume that it is in the main module
add input modules that takes its MAI data element
closer to the raw input
add transform modules in order to transform the raw
input into the desired MAI data element

45. Example: additional factoring of the word
count program

46. Contd…
Output modules are treated in a similar fashion,
this time working from MAO data elements to
the raw output of the system
Central transforms are also factored in a
stepwise manner until you have specified
atomic modules that can be implemented
directly

47. Example: additional factoring of the
word count program

48. SDM Wrap-Up
Each new module produced in step 4 can then
be examined to see if additional factoring is
necessary

49. Design Heuristics
The strategy requires the designer to exercise sound
judgment and common sense
Cohesion and coupling should be the primary guiding
factors
A very high fan-out is not very desirable (control and
coordinate more modules)
Fan-in should be maximized
Scope of effect of a decision should be subset of the
scope of control.

50. Verification
Designs should be checked for internal consistency and
for completeness with respect to the SRS
If a formal design notation is used, then tools may be
able to perform some of these checks (Automated
Cross Checking)
Otherwise, design reviews (as part of your inspection
process) are required to ensure that the finished design is
of high quality

51. Design Reviews
To ensure “quality” of the design
Aim of design reviews – detecting errors in design
Review team – a member of both the system design team and
the detailed design team, the author of the requirements
document, the author responsible for maintaining the design
document, and an independent software quality engineer.

52. Metrics
To provide quantitative data to the management process
Cost and schedule metrics are needed for tracking the
progress of the project
Size is always a product metric of interest
Size: Number of Modules x Average LOC expected per
module
Or you can generate LOC estimates for each individual
module

53. Metrics
Quality metrics
Simplicity – most important design quality attribute
Complexity metrics
Network Metrics
Stability Metrics
Information Flow Metrics

54. Network Metrics
Network metrics focus on the structure chart of a system
They attempt to define how “good” the structure or network is in
an effort to quantify the complexity of the call graph
The simplest structure occurs if the call graph is a tree.
As a result, the graph impurity (deviation of the tree) is
defined as nodes - edges - 1
In the case of a tree, this metric produces the result zero
since there is always one more node in a tree than edges
This metric is designed to make you examine nodes that
have high coupling and see if there are ways to reduce this
coupling

55. Stability Metrics
Stability of a design is a metric that tries to quantify the
resistance of a design to the potential ripple effects that
are caused by changes in modules
The creators of this metric argue that the higher the stability
of a design, the easier it is to maintain the resulting system
This provides a stability value for each particular module
In essence, the lower the amount of coupling between
modules, the higher the stability of the overall system

56. Information Flow Metrics
Information flow metrics attempt to define the
complexity of a system in terms of the total
amount of information flowing through its
modules
Jalote discusses two information flow metrics
and how they can be used to classify modules

57. Approach 1
A module's complexity depends on its intramodule complexity and its
intermodule complexity
intramodule complexity is approximated by the (estimated) size of the
module in lines of code
intermodule complexity is determined by the total amount of information
(abstract data elements) flowing into a module (inflow) and the total
amount of information flowing out of a module (outflow)
The module design complexity Dc is defined as Dc = size *
(inflow*outflow)
2
The term (inflow*outflow)
2
refers to the total number of input and output
combinations, and this number is squared since the interconnections
between modules are considered more important to determining the
complexity of a module than its code size

58. Approach 2
Approach 1 depends largely on the amount of information flowing in and
out of the module
Approach 2 is a variant that also considers the number of modules
connected to a particular module; in addition, the code size of a module
is considered insignificant with respect to a module's complexity
The module design complexity Dc is defined as Dc = (fan_in * fan_out)
+ (inflow*outflow)
fan_in above refers to the number of modules that call this module,
fan_out is the number of modules called by this module

59. Classification
Neither of these metrics is any good, unless they can tell us when to
consider a module “too complex”
To this end, an approach was developed to compare a module's
complexity against the complexity of the other modules in its system
avg_complexity is defined as the average complexity of the modules
in the current design
std_deviation is defined as the standard deviation in the design
complexity of the modules in the current design
A module can be classified as error prone, complex, or normal using
the following conditions
Dc is the complexity of a particular module
A module is error prone if Dc > avg_complexity + std_deviation
A module is complex if avg_complexity < Dc < avg_complexity +
std_deviation
Otherwise a module is considered normal