Dr. E.F.Codd’s Rules

Dr. E.F.Codd’s Rules

1. The information rule:-

            All the data should be presented in table form.

2. Guaranteed access rule:-

            All data should be accessible without ambiguity(doubt). This can be accomplished through a combination of the table name , primary key, and column name.

3. Systematic treatment of NULL values:-

            A field should be allowed to remain empty. This involves the support of a null value, which is distinct from an empty string or a number with a value of zero. This can’t apply to primary key. Most database implementation support the concept of a not null field constraint that prevents null values in a specific table column.

4.Dynamic online catalog based on the relational model:-

            A relational database must provide access to its structure through the same tools that are used to access the data. This is usually accomplished by storing the structure definition within special system tables.

5.Comprehensive data sublanguage rule:-

            The database must support at least one clearly defined language that includes functionality for a data definition , data manipulation , data integrity and database transaction control. All commercial relational databases are use forms of standard SQL (i.e. structured query language) as their supported comprehensive language.

6.View updating rule:-

            Data can be presented in different logical combinations called views. Each view should support the same full range of data manipulation that has direct access to a table available. In a practice, providing update and delete access to logical views is difficult and is not fully supported by any current database.

7.High-level insert, update & delete:-

            Data can be retrieved from a relational database in sets constructed of data from multiple rows and / or multiple tables. This rule state that insert  , update and delete operations should be supported for any retrievable set rather than just for a single row in a single table.

8.Physical data Independence:-

            This user is isolated from the physical method of storing and retrieving information from the database. Changes can be made to the underlying architecture ( hardware disk storage method) without affecting how the user access it.

9.Logical data Independence:-

            How data is viewed should not be changed when the logical structure (table’s structure) of the database changes. This rule is particularly difficult to satisfy most database rely on strong ties between the data viewed and the actual structure of the underlying  tables.

10. Integrity Independence:-

            The database language (like SQL) should support constraint on user input that maintain database integrity. This rule is not fully implemented by most major vendors. At a minimum , all database do preserve two constraints through SQL. No component of primary key can have null value. If a foreign key is defined in one table any value in it must exist as a primary key in another table.

11. Distribution Independence:-

            A user should be totally unaware of whether or not the database is distributed . a verity of reasons make this rule difficult to implement.

12. Non Subversion Rule:-

            There should be no way to modify the database structure other than through the multiple row database language (like SQL)  Most database support administrative tolls that allow some direct manipulation of the data structure.

Importance of E.R Diagram in RDBMS

• ER-modeling is a data modeling technique used in software engineering to produce a conceptual data model of information system.
• Diagrams created using this ER-modeling technique are called Entity-Relationship Diagrams, or ER diagrams or ERDs. So you can say that Entity Relationship Diagrams illustrate the logical structure of databases.
• Dr. Peter Chen is the originator of the Entity-Relationship Model.
• His original paper about ER-modeling is one of the most cited papers in the computer software field.
• Currently the ER model serves as the foundation of many system analysis and design methodologies, computer-aided software engineering (CASE) tools, and repository systems.