Testing Metrics

While testing a product, test manager has to take a lot of decisions like when to stop testing or when is the application ready for production, how to track testing progress, how to measure the quality of a product at a certain point in the testing cycle?Testing metrics can help to take better and accurate decisions

Lets start by defining the term 'Metric'
A metric is a mathematical number that shows a relationship between two variables. Software metrics are measures used to quantify status or results.

How to track testing progress?
The best way is to have a fixed number of test cases ready before test execution cycle begins.Then the testing progress is measured by the total number of test cases executed.

% Completion = (Number of test cases executed)/(Total number of test cases)

Not only the testing progress but also the following metrics are helpful to measure the quality of the product
% Test cases Passed = (Number of test cases Passed)/(Number of test cases executed)

% Test cases Failed = (Number of test cases Passed)/(Number of test cases executed)
Note: A test case is Failed when atleast one bug is found while executing it, otherwise Passed

How many rounds or cycles of testing should be done?
or
When to stop testing?
Lets discuss few approaches
Approach 1:This approache requires, that you have a fixed number of test cases ready before test execution cycle.In each testing cycle you execute all test cases.You stop testing when all the test cases are Passed or % failure is very very less in the latest testing cycle.

Approach 2:Make use of the following metrics
Mean Time Between Failure: The average operational time it takes before a software system fails.
Coverage metrics: the percentage of instructions or paths executed during tests.
Defect density: defects related to size of software such as “defects/1000 lines of code” Open bugs and their severity levels,

If the coverage of code is good, Mean time between failure is quite large, defect density is very ow and not may high severity bugs still open, then 'may' be you should stop testing. 'Good', 'large', 'low' and 'high' are subjective terms and depends on the product being tested.Finally, the risk associated with moving the application into production, as well as the risk of not moving forward, must be taken into consideration.