5

Question 1

Changelog

Answer 1

Includes why

Question 2

Sql dialects

Answer 2

Standard sql
Postgre sgl
My sql
Sql server

Question 3

Data validation types

Answer 3

Type
Range
Constraints
Consistency
Structure
Code validation

Question 4

Validating type

Answer 4

Ensuring all data types are uniformPurpose: Check that the data matches the data type defined for a field.

Example: Data values for school grades 1-12 must be a numeric data type.

Limitations: The data value 13 would pass the data type validation but would be an unacceptable value. For this case, data range validation is also needed.

Question 5

Validating range

Answer 5

Purpose: Check that the data falls within an acceptable range of values defined for the field.

Example: Data values for school grades should be values between 1 and 12.

Limitations: The data value 11.5 would be in the data range and would also pass as a numeric data type. But, it would be unacceptable because there aren’t half grades. For this case, data constraint validation is also needed.

Question 6

Validating data constraints

Answer 6

Purpose: Check that the data meets certain conditions or criteria for a field. This includes the type of data entered as well as other attributes of the field, such as number of characters.

Example: Content constraint: Data values for school grades 1-12 must be whole numbers.

Limitations: The data value 13 is a whole number and would pass the content constraint validation. But, it would be unacceptable since 13 isn’t a recognized school grade. For this case, data range validation is also needed.

Question 7

Validate data consistency

Answer 7

Purpose: Check that the data makes sense in the context of other related data.

Example: Data values for product shipping dates can’t be earlier than product production dates.

Limitations: Data might be consistent but still incorrect or inaccurate. A shipping date could be later than a production date and still be wrong.

Question 8

Validate data structure

Answer 8

Purpose: Check that the data follows or conforms to a set structure.

Example: Web pages must follow a prescribed structure to be displayed properly.

Limitations: A data structure might be correct with the data still incorrect or inaccurate. Content on a web page could be displayed properly and still contain the wrong information.

Question 9

Code validation

Answer 9

Purpose: Check that the application code systematically performs any of the previously mentioned validations during user data input.

Example: Common problems discovered during code validation include: more than one data type allowed, data range checking not done, or ending of text strings not well defined.

Limitations: Code validation might not validate all possible variations with data input.