Se Unit 3
Se Unit 3
Interface Design:
        Interface design is the specification of the interaction between a system and its environment.
this phase proceeds at a high level of abstraction with respect to the inner workings of the system i.e,
during interface design, the internal of the systems are completely ignored and the system is treated
as a black box. Attention is focussed on the dialogue between the target system and the users,
devices, and other systems with which it interacts. The design problem statement produced during
the problem analysis step should identify the people, other systems, and devices which are
collectively called agents.
Interface design should include the following details:
  ● Precise description of events in the environment, or messages from agents to which the system
      must respond.
  ● Precise description of the events or messages that the system must produce.
  ● Specification on the data, and the formats of the data coming into and going out of the system.
  ● Specification of the ordering and timing relationships between incoming events or messages,
      and outgoing events or outputs.
Architectural Design:
        Architectural design is the specification of the major components of a system, their
responsibilities, properties, interfaces, and the relationships and interactions between them. In
architectural design, the overall structure of the system is chosen, but the internal details of major
components are ignored.
Issues in architectural design includes:
  ● Gross decomposition of the systems into major components.
  ● Allocation of functional responsibilities to components.
  ● Component Interfaces
  ● Component scaling and performance properties, resource consumption properties, reliability
      properties, and so forth.
  ● Communication and interaction between components.
The architectural design adds important details ignored during the interface design. Design of the
internals of the major components is ignored until the last phase of the design.
Detailed Design:
        Design is the specification of the internal elements of all major system components, their
properties, relationships, processing, and often their algorithms and the data structures.
The detailed design may include:
  ● Decomposition of major system components into program units.
  ● Allocation of functional responsibilities to units.
  ● User interfaces
  ● Unit states and state changes
  ● Data and control interaction between units
  ● Data packaging and implementation, including issues of scope and visibility of program
      elements
  ● Algorithms and data structures
          The design process should not suffer from “tunnel vision.” A good designer should
        consider alternative approaches, judging each based on the requirements of the problem, the
        resources available to do the job.
         The design should be traceable to the analysis model. Because a single element of
      the design model often traces to multiple requirements, it is necessary to have a means for
      tracking how requirements have been satisfied by the design model.
         The design should not reinvent the wheel. Systems are constructed using a set of
      design patterns, many of which have likely been encountered before. These patterns should
      always be chosen as an alternative to reinvention. Time is short and resources are limited!
      Design time should be invested in representing truly new ideas and integrating those patterns
      that already exist.
             The design should “minimize the intellectual distance” between the software and
           the problem as it exists in the real world. That is, the structure of the software design
           should (whenever possible) mimic the structure of the problem domain.
   
              The design should exhibit uniformity and integration. A design is uniform if it appears
           that one person developed the entire thing. Rules of style and format should be defined for a
           design team before design work begins. A design is integrated if care is taken in defining
           interfaces between design components.
   
              The design should be structured to accommodate change. The design concepts
           discussed in the next section enable a design to achieve this principle.
   
              The design should be structured to degrade gently, even when aberrant data,
           events, or operating conditions are encountered. Well- designed software should never
           “bomb.” It should be designed to accommodate unusual circumstances, and if it must
           terminate processing, do so in a graceful manner.
   
             Design is not coding, coding is not design. Even when detailed procedural designs are
           created for program components, the level of abstraction of the design model is higher than
           source code. The only design decisions made at the coding level address the small
           implementation details that enable the procedural design to be coded.
   
             The design should be assessed for quality as it is being created, not after the fact. A
          variety of design concepts and design measures are available to assist the designer in
          assessing quality.
         The design should be reviewed to minimize conceptual (semantic) errors. There is
   sometimes a tendency to focus on minutiae when the design is reviewed, missing the forest for the
   trees. A design team should ensure that major conceptual elements of the design (omissions,
   ambiguity, inconsistency) have been addressed before worrying about the syntax of the design
   model.
   Design concepts
   The set of fundamental software design concepts are as follows:
   1. Abstraction
   An abstraction is a tool that enables a designer to consider a component at an abstract level without
   bothering about the internal details of the implementation. Abstraction can be used for existing
   element as well as the component being designed.
   Here, there are two common abstraction mechanisms
        1. Functional Abstraction
        2. Data Abstraction
   Functional Abstraction
      i. A module is specified by the method it performs.
     ii. The details of the algorithm to accomplish the functions are not visible to the user of the
            function.
   Functional abstraction forms the basis for Function oriented design approaches.
   Data Abstraction
   Details of the data elements are not visible to the users of data. Data Abstraction forms the basis
   for Object Oriented design approaches
   2. Architecture
● The complete structure of the software is known as software architecture.
● Structure provides conceptual integrity for a system in a number of ways.
● The architecture is the structure of program modules where they interact with each other in a
   specialized way.
● The components use the structure of data.
● The aim of the software design is to obtain an architectural framework of a system.
● The more detailed design activities are conducted from the framework.
     3. Patterns
     A design pattern describes a design structure and that structure solves a particular design problem in
     a specified content.
     4. Modularity
● A software is separately divided into name and addressable components. Sometime they are called
     as modules which integrate to satisfy the problem requirements.
● Modularity is the single attribute of a software that permits a program to be managed easily.
     5. Information hiding
     Modules must be specified and designed so that the information like algorithm and data presented in
     a module is not accessible for other modules not requiring that information.
     6. Functional independence
● The functional independence is the concept of separation and related to the concept of modularity,
     abstraction and information hiding.
● The functional independence is accessed using two criteria i.e Cohesion and coupling.
     Cohesion
● Cohesion is an extension of the information hiding concept.
● A cohesive module performs a single task and it requires a small interaction with the other
     components in other parts of the program.
     Coupling
     Coupling is an indication of interconnection between modules in a structure of software.
     7. Refinement
●   Refinement is a top-down design approach.
●   It is a process of elaboration.
●   A program is established for refining levels of procedural details.
●   A hierarchy is established by decomposing a statement of function in a stepwise manner till the
     programming language statement are reached.
     8. Refactoring
●   It is a reorganization technique which simplifies the design of components without changing its
     function behaviour.
●   Refactoring is the process of changing the software system in a way that it does not change the
     external behaviour of the code still improves its internal structure.
     9. Design classes
●   The model of software is defined as a set of design classes.
●   Every class describes the elements of problem domain and that focus on features of the problem
     which are user visible.
Modularization
Modularization is a technique to divide a software system into multiple discrete and independent
modules, which are expected to be capable of carrying out task(s) independently. These modules
may work as basic constructs for the entire software. Designers tend to design modules such that
they can be executed and/or compiled separately and independently.
Modular design unintentionally follows the rules of ‘divide and conquer’ problem-solving strategy this
is because there are many other benefits attached with the modular design of a software.
Advantage of modularization:
     ● Smaller components are easier to maintain
     ● Program can be divided based on functional aspects
     ● Desired level of abstraction can be brought in the program
     ● Components with high cohesion can be re-used again
     ● Concurrent execution can be made possible
     ● Desired from security aspect
Concurrency
Back in time, all software are meant to be executed sequentially. By sequential execution we mean
that the coded instruction will be executed one after another implying only one portion of program
being activated at any given time. Say, a software has multiple modules, then only one of all the
modules can be found active at any time of execution.
In software design, concurrency is implemented by splitting the software into multiple independent
units of execution, like modules and executing them in parallel. In other words, concurrency provides
capability to the software to execute more than one part of code in parallel to each other.
It is necessary for the programmers and designers to recognize those modules, which can be made
parallel execution.
Example
The spell check feature in word processor is a module of software, which runs along side the word
processor itself.
Coupling and Cohesion
When a software program is modularized, its tasks are divided into several modules based on some
characteristics. As we know, modules are set of instructions put together in order to achieve some
tasks. They are though, considered as single entity but may refer to each other to work together.
There are measures by which the quality of a design of modules and their interaction among them
can be measured. These measures are called coupling and cohesion.
Cohesion
Cohesion is a measure that defines the degree of intra-dependability within elements of a module.
The greater the cohesion, the better is the program design.
There are seven types of cohesion, namely –
     ● Co-incidental cohesion - It is unplanned and random cohesion, which might be the result of
        breaking the program into smaller modules for the sake of modularization. Because it is
        unplanned, it may serve confusion to the programmers and is generally not-accepted.
     ● Logical cohesion - When logically categorized elements are put together into a module, it is
        called logical cohesion.
     ● Temporal Cohesion - When elements of module are organized such that they are processed
        at a similar point in time, it is called temporal cohesion.
     ● Procedural cohesion - When elements of module are grouped together, which are executed
        sequentially in order to perform a task, it is called procedural cohesion.
     ● Communicational cohesion - When elements of module are grouped together, which are
        executed sequentially and work on same data (information), it is called communicational
        cohesion.
     ● Sequential cohesion - When elements of module are grouped because the output of one
        element serves as input to another and so on, it is called sequential cohesion.
     ● Functional cohesion - It is considered to be the highest degree of cohesion, and it is highly
        expected. Elements of module in functional cohesion are grouped because they all contribute
        to a single well-defined function. It can also be reused.
Coupling
Coupling is a measure that defines the level of inter-dependability among modules of a program. It
tells at what level the modules interfere and interact with each other. The lower the coupling, the
better the program.
There are five levels of coupling, namely -
     ● Content coupling - When a module can directly access or modify or refer to the content of
         another module, it is called content level coupling.
     ● Common coupling- When multiple modules have read and write access to some global data,
         it is called common or global coupling.
     ● Control coupling- Two modules are called control-coupled if one of them decides the
         function of the other module or changes its flow of execution.
     ● Stamp coupling- When multiple modules share common data structure and work on different
         part of it, it is called stamp coupling.
     ● Data coupling- Data coupling is when two modules interact with each other by means of
         passing data (as parameter). If a module passes data structure as parameter, then the
         receiving module should use all its components.
Ideally, no coupling is considered to be the best.
Design Verification
The output of software design process is design documentation, pseudo codes, detailed logic
diagrams, process diagrams, and detailed description of all functional or non-functional
requirements.
The next phase, which is the implementation of software, depends on all outputs mentioned above.
It is then becomes necessary to verify the output before proceeding to the next phase. The early any
mistake is detected, the better it is or it might not be detected until testing of the product. If the
outputs of design phase are in formal notation form, then their associated tools for verification
should be used otherwise a thorough design review can be used for verification and validation.
By structured verification approach, reviewers can detect defects that might be caused by
overlooking some conditions. A good design review is important for good software design, accuracy
and quality.
Problem Partitioning
For small problem, we can handle the entire problem at once but for the significant problem, divide
the problems and conquer the problem it means to divide the problem into smaller pieces so that
each piece can be captured separately.
For software design, the goal is to divide the problem into manageable pieces.
Benefits of Problem Partitioning
Software is easy to understand
Software becomes simple
Software is easy to test
Software is easy to modify
Software is easy to maintain
Software is easy to expand
These pieces cannot be entirely independent of each other as they together form the system. They
have to cooperate and communicate to solve the problem. This communication adds complexity.
   ● Entities - Entities are source and destination of information data. Entities are represented by
       a rectangles with their respective names.
   ● Process - Activities and action taken on the data are represented by Circle or Round-edged
       rectangles.
   ● Data Storage - There are two variants of data storage - it can either be represented as a
       rectangle with absence of both smaller sides or as an open-sided rectangle with only one side
       missing.
   ● Data Flow - Movement of data is shown by pointed arrows. Data movement is shown from
       the base of arrow as its source towards head of the arrow as destination.
Levels of DFD
   ● Level 0 - Highest abstraction level DFD is known as Level 0 DFD, which depicts the entire
       information system as one diagram concealing all the underlying details. Level 0 DFDs are
       also known as context level DFDs.
   ● Level 1 - The Level 0 DFD is broken down into more specific, Level 1 DFD. Level 1 DFD
       depicts basic modules in the system and flow of data among various modules. Level 1 DFD
       also mentions basic processes and sources of information.
    ● Level 2 - At this level, DFD shows how data flows inside the modules mentioned in Level 1.
        Higher level DFDs can be transformed into more specific lower level DFDs with deeper level
        of understanding unless the desired level of specification is achieved.
Structure Charts
Structure chart is a chart derived from Data Flow Diagram. It represents the system in more detail
than DFD. It breaks down the entire system into lowest functional modules, describes functions and
sub-functions of each module of the system to a greater detail than DFD.
Structure chart represents hierarchical structure of modules. At each layer a specific task is
performed.
Here are the symbols used in construction of structure charts -
    ● Module - It represents process or subroutine or task. A control module branches to more than
       one sub-module. Library Modules are re-usable and invokable from any module.
● Condition - It is represented by small diamond at the base of module. It depicts that control
   module      can    select     any    of    sub-routine    based      on    some      condition.
● Jump - An arrow is shown pointing inside the module to depict that the control will jump in the
HIPO Diagram
HIPO (Hierarchical Input Process Output) diagram is a combination of two organized method to
analyze the system and provide the means of documentation. HIPO model was developed by IBM in
year 1970.
HIPO diagram represents the hierarchy of modules in the software system. Analyst uses HIPO
diagram in order to obtain high-level view of system functions. It decomposes functions into
sub-functions in a hierarchical manner. It depicts the functions performed by system.
HIPO diagrams are good for documentation purpose. Their graphical representation makes it easier
for designers and managers to get the pictorial idea of the system structure.
In contrast to IPO (Input Process Output) diagram, which depicts the flow of control and data in a
module, HIPO does not provide any information about data flow or control flow.
Example
Both parts of HIPO diagram, Hierarchical presentation and IPO Chart are used for structure design
of software program as well as documentation of the same.
Structured English
Most programmers are unaware of the large picture of software so they only rely on what their
managers tell them to do. It is the responsibility of higher software management to provide accurate
information to the programmers to develop accurate yet fast code.
 Other forms of methods, which use graphs or diagrams, may are sometimes interpreted differently
 by different people.
 Hence, analysts and designers of the software come up with tools such as Structured English. It is
 nothing but the description of what is required to code and how to code it. Structured English helps
 the programmer to write error-free code.
 Other form of methods, which use graphs or diagrams, may are sometimes interpreted differently by
 different people. Here, both Structured English and Pseudo-Code tries to mitigate that
 understanding gap.
 Structured English is the It uses plain English words in structured programming paradigm. It is not
 the ultimate code but a kind of description what is required to code and how to code it. The following
 are some tokens of structured programming.
IF-THEN-ELSE,
DO-WHILE-UNTIL
 Analyst uses the same variable and data name, which are stored in Data Dictionary, making it much
 simpler to write and understand the code.
Example
 We take the same example of Customer Authentication in the online shopping environment. This
 procedure to authenticate customer can be written in Structured English as:
Enter Customer_Name
SEEK Customer_Name in Customer_Name_DB file
IF Customer_Name found THEN
   Call procedure USER_PASSWORD_AUTHENTICATE()
ELSE
   PRINT error message
   Call procedure NEW_CUSTOMER_REQUEST()
ENDIF
 The code written in Structured English is more like day-to-day spoken English. It can not be
 implemented directly as a code of software. Structured English is independent of programming
 language.
Pseudo-Code
 Pseudo code is written more close to programming language. It may be considered as augmented
 programming language, full of comments and descriptions.
 Pseudo code avoids variable declaration but they are written using some actual programming
 language’s constructs, like C, Fortran, Pascal etc.
 Pseudo code contains more programming details than Structured English. It provides a method to
 perform the task, as if a computer is executing the code.
Example
 Program to print Fibonacci up to n numbers.
void function Fibonacci
Get value of n;
Set value of a to 1;
Set value of b to 1;
Initialize I to 0
for (i=0; i< n; i++)
{
   if a greater than b
   {
      Increase b by a;
      Print b;
   }
   else if b greater than a
   {
      increase a by b;
      print a;
   }
}
Decision Tables
A Decision table represents conditions and the respective actions to be taken to address them, in a
structured tabular format.
It is a powerful tool to debug and prevent errors. It helps group similar information into a single table
and then by combining tables it delivers easy and convenient decision-making.
Creating Decision Table
To create the decision table, the developer must follow basic four steps:
     ● Identify all possible conditions to be addressed
     ● Determine actions for all identified conditions
     ● Create Maximum possible rules
     ● Define action for each rule
Decision Tables should be verified by end-users and can lately be simplified by eliminating duplicate
rules and actions.
Example
Let us take a simple example of day-to-day problem with our Internet connectivity. We begin by
identifying all problems that can arise while starting the internet and their respective possible
solutions.
We list all possible problems under column conditions and the prospective actions under column
Actions.
                          Conditions/Actions                                Rules
                          Shows Connected                                      N N N N Y Y Y Y
Conditions                Ping is Working                                      N N Y Y N N Y Y
                          Opens Website                                        Y N Y N Y N Y N
                          Check network cable                                  X
                          Check internet router                                X            X X X
Actions                   Restart Web Browser                                                   X
                          Contact Service provider                                 X X X X X X
                          Do no action
Table : Decision Table – In-house Internet Troubleshooting
Entity-Relationship Model
Entity-Relationship model is a type of database model based on the notion of real world entities and
relationship among them. We can map real world scenario onto ER database model. ER Model
creates a set of entities with their attributes, a set of constraints and relation among them.
ER Model is best used for the conceptual design of database. ER Model can be represented as
follows :
    ● Entity - An entity in ER Model is a real world being, which has some properties
       called attributes. Every attribute is defined by its corresponding set of values,
       called domain.
       For example, Consider a school database. Here, a student is an entity. Student has various
       attributes like name, id, age and class etc.
    ● Relationship - The logical association among entities is called relationship. Relationships
       are mapped with entities in various ways. Mapping cardinalities define the number of
       associations between two entities.
       Mapping cardinalities:
           o one to one
           o one to many
           o many to one
           o many to many
Data Dictionary
Data dictionary is the centralized collection of information about data. It stores meaning and origin of
data, its relationship with other data, data format for usage etc. Data dictionary has rigorous
definitions of all names in order to facilitate user and software designers.
Data dictionary is often referenced as meta-data (data about data) repository. It is created along with
DFD (Data Flow Diagram) model of software program and is expected to be updated whenever DFD
is changed or updated.
Requirement of Data Dictionary
The data is referenced via data dictionary while designing and implementing software. Data
dictionary removes any chances of ambiguity. It helps keeping work of programmers and designers
synchronized while using same object reference everywhere in the program.
Data dictionary provides a way of documentation for the complete database system in one place.
Validation of DFD is carried out using data dictionary.
Contents
Data dictionary should contain information about the following
    ● Data Flow
    ● Data Structure
    ● Data Elements
    ● Data Stores
    ● Data Processing
Data Flow is described by means of DFDs as studied earlier and represented in algebraic form as
described.
=                 Composed of
{}                  Repetition
()                  Optional
+                   And
[/]                 Or
 Example
 Address = House No + (Street / Area) + City + State
 Course ID = Course Number + Course Name + Course Level + Course Grades
 Data Elements
 Data elements consist of Name and descriptions of Data and Control Items, Internal or External data
 stores etc. with the following details:
     ● Primary Name
     ● Secondary Name (Alias)
     ● Use-case (How and where to use)
     ● Content Description (Notation etc. )
     ● Supplementary Information (preset values, constraints etc.)
 Data Store
 It stores the information from where the data enters into the system and exists out of the system.
 The Data Store may include -
     ● Files
             o Internal to software.
             o External to software but on the same machine.
             o External to software and system, located on different machine.
     ● Tables
             o Naming convention
             o Indexing property
 Data Processing
 There are two types of Data Processing:
     ● Logical: As user sees it
     ● Physical: As software sees it
    ● Radio-button - Displays available options for selection. Only one can be selected among all
       offered.
    ● Check-box - Functions similar to list-box. When an option is selected, the box is marked as
       checked. Multiple options represented by check boxes can be selected.
    ● List-box - Provides list of available items for selection. More than one item can be selected.