INTRODUCTION TO DATABASE DESIGN:-

* SDLC

* DDLC

* SSAD

* SOFTWARE DEVELOPMENT COST

* DATABASE DESIGN

* AUTOMATED DESIGN TOOLS

SOFTWARE DEVELOPMENT LIFE CYCLE (SDLC):-

It is a proper engineering framework that is essential for developing reliable, maintainable and cost effective application and other software.

It start with concept exploration and end when the product is finally retired.

From the start to the end the product goes through a series of phases and finally retires.

By many variations, the software life cycle can be partitioned into the following phases.

1) Requirements Phase (or Concept) phase

2) Specification Phase

3) Planning phase

4) Design Phase

5) Programming (or Coding or Implementation) Phase

6) Integration (or Testing) Phase

7) Maintenance Phase

8) Retirement Phase

Requirements (or Concept) Phase:-

It is in which the concept is explored and refined.

The client’s requirements are also analysed.

Specification Phase:-

It is in which the client’s requirements are presented in the form of specification document.

Planning Phase:-

It is in which a plan (software Project Management Plan), is drawn up.

Design Phase:-

It undergoes two consecutive design process.

1) Global Design phase (modules)

2) Detailed Design phase (design of each Module)

Programming (or Coding or Implementation) Phase:-

It is in which the various modules (or components) of the software are coded in a specific computer programming language.

Integration (or Testing) Phase:-

It is in which components are tested individually and combined and then tested as a whole.

once accepted, it goes into operations mode.

Maintenance Phase:-

It is in which all corrective maintenance is done.

Retirement Phase:-

It is in which the software product is removed from the service.

SOFTWARE DEVELOPMENT COST

3% 4% 2%

6%5%

7%

6%67%

dev.costRequirements

Specification

Planning

Desing

Module Coding

Module Testing

Integration Testing

Maintenance

STRUCTURED SYSTEM ANALYSIS AND DESIGN (SSAD)

It is a software engineering approach to the specification, design, construction, testing and maintenance of software for maximizing the reliability and maintainability of the system as well as for reducing the software life-cycle costs.

Two approaches are considered and used.

1) Structured System Analysis

2) Structured Design.

The following steps are involved in structured analysis:-

Step 1:-Draw the Data Flow Diagram (DFD)

Step 2:-Put in the details of data flow

Step 3:-Define the logic of processesses

Step 4:-Define data Store

Step 5:-Define the physical resources

Step 6:-Determine the input/output specifications

Step 7:-Perform Sizing

Step 8:-Determine the hardware requirements

Structured Design:-

It is a specific approach to the design process that results in small, independent, black-box modules, arranged in a hierarchy in a top-down fashion.

It uses the following tools to build the systems specifications document:

1) Cohesion2) Coupling3) Data flow analysis

Cohesion of a component is a measure of how well it fits together.

It performs a single task within a software procedure.

It requires little interaction with procedures being performed in other parts of a program.

It is the degree of interaction between two modules.

It has a low degree of cohesion.

Coupling is a measure of interconnections among modules in software.

It is the degree of interaction between two software modules.

It has high degree of coupling.

Data Flow Analysis (DFA) is a design method of achieving software modules with high cohesion.

It can be used in conjunction with most specification methods, such as structured system analysis.

The input to DFA is a Data Flow Diagram (DFD).

DATABASE DEVELOPMENT LIFE CYCLE:-

It is a process of designing, implementing and maintaining a database system to meet strategic or operational information needs of an organization or enterprise such as

1) Improved Customer support and customer Satisfaction.

2) Better Production management

3) Better inventory management

4) More accurate sale forecasting.

The following are the various stages of database development life cycle (DDLC) and include the following steps.

1) Feasibility Study and requirement analysis

2) Database implementation

3) Data and application conversion

4) Testing and validation

5) Monitoring and maintenance

Feasibility study and

requriement analysis

Monitoring and

Maintenance

Database Design

Data and Application Conversion

Testing and

Validation

Database Implementation

DATABASE DESIGN:-

It is a process of designing the logical and physical structure of one or more databases.

There are many approaches to the design of a database .

1) Bottom-up approach2) Top-down approach3) Inside-out approach4) Mixed strategy approach

Bottom up database approach:-

It starts at the fundamental level of attributes (or abstractions)

It starts with properties of entities and relationships.

It them combines and forms into group of relations that represent types of entities and relationships between entities.

Top-down database design approach:-

It starts with the development of data models (or schemas)

It contains high-level abstractions (entities and relationships).

Then the successive top down refinements are applied to identify lower level entities, relationships, and the associated attributes.

Inside-out database design approach:-

It starts with the identification of set of major entities

It then spreads out to consider other entities, relationships and attributes associated with those first identified.

It is a special case of bottom-up approach.

Mixed Strategy database design approach:-

It uses both the bottom-up and top-down approach.

The requirements are partitioned according to a top-down approach

Part of the schema is designed for each partition according to a bottom-up approach.

Then all the schema parts are combined together.

The following are the phases involved in the good database design.

1) Data requirements collection and analysis

2) Conceptual database design

3) DBMS selection

4) Logical database design

5) Physical database design

6) Prototyping

7) Database implementation and tuning

AUTOMATED DESIGN TOOLS:-

The overall database design activity has to undergo a systematic process called design methodology.

In the early days it was done manually by the experienced and knowledgeable database designers.

Limitations of Manual Database Design:-

1) Difficulty in dealing with the increased number of alternative design to model the same information and more complex data in terms of relationships and constraints.

2) Making the task of managing manual designs almost impossible for ever increasing size of the databases, their entity types and relationship types.

COMPUTER-AIDED SOFTWARE ENGINEERING (CASE) TOOLS:-

The limitations gave rise to CASE.

They are the software that provides automated support for some portion of the system development process.

They help the DBA.

They help the designer to draw the data models using E-R diagrams.

CASE tools may be categorized into the following three application levels to automate various stages of development life-cycle.

1) Upper-CASE tools

2) Lower-CASE tools.

3) Integrated-CASE tools.

Upper-CASE tools support the initial stages of DDLC, i.e. from feasibility study and requirement analysis through the database design.

Lower-CASE tools support the later stages of DDLC, i.e. from database implementation through testing, to monitoring and maintenance.

Integrated-CASE tools support all stages of the DDLC and provides the functionality of both Upper-CASE and Lower-CASE in one tool.

Facilities provided by the CASE tools:-

1) Create a data dictionary to store information

2) Design tools to support data analysis

3) Tools to permit development of the corporate data model and the conceptual and logical data models.

4) To help in drawing conceptual schema diagram using entity-relationship .

5) Generate schemas (or codes) in SQL DDL for mapping and implementing algorithms.

6) Decomposition and Normalization.

7) Indexing

8) Tools to enable prototyping of applications.

9) Performance monitoring and measurement.