To test a product a test manager has to take a number of decisions such as when to start test and when to stop test or when the software development applications is complete for production, how to track the entire product at a certain point in the testing cycle. Testing metrics can help to take better and software development appropriate decisions.
What is Metric?
A metric defined as a mathematical number which shows an association among two variables. Software metrics are actions utilized to enumerate grade or results.
How to track testing progress?
The most efficient method is to have a fixed number of test cases prepared before starting the test execution. Then the test growth is calculated by the total number of test cases executed. Following shows to calculate the completions software development progress:
Percentage of Completion = Total number of test cases executed/ Total number of test cases
Testing progress is very much helpful to measure quality of the product. Other then this following metrics are also helpful to measure the quality the product:
Percentage of Test cases Passed = Total Number of test
cases Passed/ Total Number of test cases executed
Percentage of Test cases Failed = Total Number of test cases Passed/ Total
Number of test cases executed
process metrics for software testing
How many numbers of cycles of testing ought to be performed?
Some of the approaches are listed below:
Approach 1: This approached needs that you must planned a fix number of test cases before moving to the carry test executions cycle. You stop testing when all the test cases are finished or % breakdown is very less in the current testing cycle.
Approach 2: Make use of the following metrics Mean Time between Failures: The average operational time it acquire before software system fails.
Coverage metrics: The fraction of instructions or paths performs during tests.
Bug density: Bugs related to size of software like “defects/1000 lines of code” Open bugs and their severity levels,
If the reporting of code is fine, Mean time between software development failures is reasonably large, defect density is very own and not may high harshness bugs still open, then ‘may’ be you must stop testing. ‘Low’, ‘high’ ‘good’, ‘large’, and are subjective terms and depend on the product being tested. At last, the risk linked with moving the application into production, in addition to the risk of not moving forward, should take into deliberation.
