Object-oriented programming (OOP) is a computer programming model that organizes software design around data, or objects, rather than functions and logic. An object can be defined as a data field that has unique attributes and behavior. OOP focuses on the objects that developers want to manipulate rather than the logic required to manipulate them. This approach to programming is well-suited for programs that are large, complex and actively updated or maintained. This includes programs for manufacturing and design, as well as mobile applications; for example, OOP can be used for manufacturing system simulation software.

1. Nadar Saraswathi College Arts and Science, Theni.
OBJECT ORIENTED ANALYSIS AND DESIGN
TOPIC: Design classes
BY.,
G.NIBIYA.,II-MSC(IT)

2. Data management system
Introduction:
A database management system (or DBMS) is essentially nothing more than a computerized
data-keeping system. Users of the system are given facilities to perform several kinds of
operations on such a system for either manipulation of the data in the database or the
management of the database structure itself. Database Management Systems (DBMSs) are
categorized according to their data structures or types.

3. Types
There are several types of databases that can be used on a mainframe to exploit z/OS®: inverted
list, hierarchic, network, or relational.
Mainframe sites tend to use a hierarchical model when the data structure (not data values) of
the data needed for an application is relatively static. For example, a Bill of Material (BOM)
database structure always has a high level assembly part number, and several levels of
components with subcomponents. The structure usually has a component forecast, cost, and
pricing data, and so on. The structure of the data for a BOM application rarely changes, and new
data elements (not values) are rarely identified. An application normally starts at the top with
the assembly part number, and goes down to the detail components.

4. What structures exist in a relational database?
Database
A database is a logical grouping of data. It contains a set of related table spaces and index
spaces. Typically, a database contains all the data that is associated with one application or
with a group of related applications. You could have a payroll database or an inventory
database, for example.

5. table
A table is a logical structure made up of rows and columns. Rows have no fixed order, so if you retrieve data
you might need to sort the data. The order of the columns is the order specified when the table was
created by the database administrator. At the intersection of every column and row is a specific data item
called a value, or, more precisely, an atomic value. A table is named with a high-level qualifier of the
owner's user ID followed by the table name, for example TEST.DEPT or PROD.DEPT. There are three
types of tables:
• A base table that is created and holds persistent data
• A temporary table that stores intermediate query results
• A results table that is returned when you query tables.

6. index
An index is an ordered set of pointers to rows of a table. Unlike the rows of a table that are not in a specific
order, an index must always be maintained in order by DB2®. An index is used for two purposes:
• For performance, to retrieve data values more quickly
• For uniqueness.
By creating an index on an employee's name, you can retrieve data more quickly for that employee than by
scanning the entire table. Also, by creating a unique index on an employee number, DB2 will enforce the
uniqueness of each value. A unique index is the only way DB2 can enforce uniqueness.
Creating an index automatically creates the index space, the data set that contains the index.

7. keys
A key is one or more columns that are identified as such in the creation of a table or index, or in the definition of
referential integrity.
Primary key
A table can only have one primary key because it defines the entity. There are two requirements for a primary key:
1. It must have a value, that is, it cannot be null.
2. It must be unique, that is, it must have a unique index defined on it.

8. Unique key
We already know that a primary key must be unique, but it is possible to have more than one unique key in a table. In our
EMP table example, the employee number is defined as the primary key and is therefore unique. If we also had
a social security value in our table, hopefully that value would be unique. To guarantee this, you could create a
unique index on the social security column.
Foreign key
A foreign key is a key that is specified in a referential integrity constraint to make its existence dependent on a primary or
unique key (parent key) in another table.

9. Data organization access control
What is data access control?
Data access control is a technique used to regulate employees access to files in an organization.
It involves leveraging the principle of least privilege (POLP), i.e., managing employees' access
rights based on their roles in the organization, and defining and limiting what data they have
access to.

10. Types of data access control
Organizations have to select a data access control policy that will best meet their requirements.
There are four types of access control systems set apart by how the permissions are assigned to
users.

11. Mandatory access control (MAC):
This access model makes use of a central authority to assign access rights to all employees. The
administrator classifies system resources and users based on their risk level and access
requirements. The access to resources is based on the privileges that the user possesses.
The MAC model provides a high level of data protection and is used by government agencies to
secure highly classified information. While it provides a high level of protection, the MAC model
is difficult to set up and use, which is why it is usually used along with other access models like
discretionary access control (DAC).

12. Discretionary access control (DAC):
In a DAC model, the data owner decides who is eligible to access their data. The owner sets
policies that determine who is authorized to access the resource, which gives this model more
flexibility and makes it perfect for small to medium-sized organizations. Also, this model is the
least restrictive, as the owner has complete control over their files. The lack of a central
authority makes this model hard to manage, as the ACL of each file has to be checked in case of
any discrepancy.

13. Role-based access control (RBAC):
The RBAC model is the most widely used control mechanism, as it aligns with the role and needs
of every individual in the organization. It uses the principle of least privilege (POLP) to assign
privileges based on the needs of an individual's role in the organization. Any user attempting to
access data outside their scope is restricted.

14. Distributed database
A distributed database is basically a database that is not limited to one system, it is spread over
different sites, i.e, on multiple computers or over a network of computers. A distributed
database system is located on various sites that don’t share physical components. This may be
required when a particular database needs to be accessed by various users globally. It needs to
be managed such that for the users it looks like one single database.

15. types
1. Homogeneous Database:
In a homogeneous database, all different sites store database identically. The operating system,
database management system, and the data structures used – all are the same at all sites.
Hence, they’re easy to manage.

16. 2. Heterogeneous Database:
In a heterogeneous distributed database, different sites can use different schema and software
that can lead to problems in query processing and transactions. Also, a particular site might be
completely unaware of the other sites. Different computers may use a different operating
system, different database application. They may even use different data models for the
database. Hence, translations are required for different sites to communicate.

17. Distributed Data Storage :
There are 2 ways in which data can be stored on different sites. These are:
1. Replication –
In this approach, the entire relationship is stored redundantly at 2 or more sites. If the entire
database is available at all sites, it is a fully redundant database. Hence, in replication, systems
maintain copies of data.

18. This is advantageous as it increases the availability of data at different sites. Also, now query
requests can be processed in parallel.
However, it has certain disadvantages as well. Data needs to be constantly updated. Any change
made at one site needs to be recorded at every site that relation is stored or else it may lead to
inconsistency. This is a lot of overhead. Also, concurrency control becomes way more complex as
concurrent access now needs to be checked over a number of sites.

19. 2. Fragmentation –
In this approach, the relations are fragmented (i.e., they’re divided into smaller parts) and each
of the fragments is stored in different sites where they’re required. It must be made sure that
the fragments are such that they can be used to reconstruct the original relation (i.e, there isn’t
any loss of data).
Fragmentation is advantageous as it doesn’t create copies of data, consistency is not a problem

20. Thank you