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What are the typical steps involved in Testing Databases
Database testing primarily involves two key activities like:
A) Organising Sandboxes
B) Developing Test Cases
Now let us discuss these two key activities in detail
A) Key Activity – 1: Organising Sandboxes: Database testing involves the need of a copy of databases which are called sandboxes. These sandboxes are of following three types
1) Functionality Sandbox:In this we check the new functionality of database and refactor the existing functionality. Then we pass the tested sandbox to the next stage, which is integrated sandbox.
2) Integrated Sandbox: In this we integrate all the sandboxes and then test the system.
3) QA sandbox: After the system is tested, sandboxes are sent for acceptance testing. This will ensure the quality of the database.
B) Key Activity – 2: Development of test cases: The step by step procedure for the development of test cases is as under:
Step – 1: Setting up of the test cases: Set up the database to a known state.
The sources of test data are
1) External test data.
2) Test scripts.
3) Test data with known values.
4) Real world data.
Step – 2: Running the test cases : The test cases are then run. The running of the database test cases is analogous to usual development testing.
Traditional Approach of Test Case Execution:
Test cases are executed on the browser side. Inputs are entered on web-input forms and data i submitted to the back-end database via the web browser interface. The results sent back to the browser are then validated against expected values.
Advantages of Traditional Approach: It is simple and no programming skill is required. It not only addresses thi functionality of stored procedures, rules, triggers and data integrity but also the functionality of application as a whole.
Disadvantages of Traditional Approach:
1) Sometimes the results sent to the browser after test case execution do no necessarily indicate that the data itself is properly written to a record in the table.
2) When erroneous results are sent back to the browser after the execution of test cases, it doesn’t necessarily mean that the error is a database error.
3) A crucial danger with database testing and with regression testing in specific is coupling between tests. If we put the database in to a known state, run several tests against that known states, before setting it, then those tests are potentially coupled to one another.
Advanced Approach of Test Case Execution:
First of all we need to do a schematic preparation for Database Testing, which involves:
Generate a list of database tables, stored procedures, triggers, defaults, rules and so on. This will help us to have a good handle on the scope of testing required for database testing.
Thereafter we can follow the following points:
1. Generate data schemata for tables. Analyzing the schema will help us determine the following:
# Can a certain field value be Null?
# What are the allowed or disallowed values?
# What are the constraints?
# Is the value dependent upon values in another table?
# Will the values of this field be in the look-up table?
# What are user defined data types?
# What are primary key and foreign key relationships among tables?
2. At a high level, analyze how the stored procedures, triggers, defaults and rules work. This will help us determine the following:
# What is the primary function of each stored procedure and trigger? Does it read data and produce outputs, write data or both?
# What are the accepted parameters?
# What are the return values?
# When is the stored procedure called and by whom?
# When is a trigger fired?
3. Determine what the configuration management process is. That is how the new tables, stored procedures, triggers and such are integrated.
Step – 3: Checking the results: Actual database test results and expected database test results are compared in this step as described in the following example.
CREATE FUNCTION f_is leapyear (@ ai_year small int)
RETURNS small int
AS
BEGIN
-if year is illegal (null or -ve ), return -1
IF (@ ai_year IS NULL) or
(@ ai_year <=0) RETURN -1
IF (((@ ai_year % ) = 0) AND
((ai_year % 100) <> 0)) OR
((ai_year % 400) = 0)
RETURN 1 -leap year
RETURN 0 – Not a leap year
END
Following test cases are derived for the above piece of code:
Test_id |
Year (Year to Test) |
Expected Result |
Observed Result |
Match |
1 |
-1 | -1 | -1 | Yes |
2 |
-400 | -1 | -1 | Yes |
3 |
100 | 0 | 0 | Yes |
4 |
1000 | 0 | 0 | Yes |
5 |
1800 | 0 | 0 | Yes |
6 |
1900 | 0 | 0 | Yes |
7 |
2010 | 0 | 0 | Yes |
8 |
400 | 1 | 1 | Yes |
9 |
1600 | 1 | 1 | Yes |
10 |
2000 | 1 | 1 | Yes |
11 |
2400 | 1 | 1 | Yes |
12 |
4 | 1 | 1 | Yes |
13 |
1204 | 1 | 1 | Yes |
14 |
1996 | 1 | 1 | Yes |
15 |
2004 | 1 | 1 | Yes |
Many More Articles & Tutorials on Databse Testing
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An Introduction to HP QuickTest Professional – QTP (3.98 Mb)
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