Quoting:
"Software testing metrics are a way to measure and monitor your test activities. More importantly, they give insights into your team’s test progress, productivity, and the quality of the system under test. When we ask ourselves “What have we tested?”, metrics will give us better answers than just “we have tested it.” Different teams measure various aspects depending on what they want to track and control or improve.
A metric usually conveys a result or a prediction based on the combination of data.
Result Metrics: metrics that are mostly an absolute measure of an activity/process completed.
Example: Time taken to run a set of test cases in a suite
Predictive Metrics: metrics that are derivatives and act as early warning signs of an unfavorable result.
Example: Defects created vs. Resolved chart shows the rate of defect fixing. This grabs the team’s attention if this rate is slower than the rate desired.
Are you using the right software test metrics? Get answers, best practices and strategies in our 14-page guide to improving your software quality through data and analytics.
Why Test Metrics? Why Should You Care?
The aim of collecting test metrics is to use the data for improving the test process, rather than to just show fancy reports. This includes finding tangible answers to the questions:
- How long will it take to test?
- How much money will it take to test?
- How bad are the bugs?
- How many bugs found were fixed? reopened? closed? deferred?
- How many bugs did the test team did not find?
- How much of the software was tested?
- Will testing be done on time? Can the software be shipped on time?
- How good were the tests? Are we using low-value test cases?
- What is the cost of testing?
- Was the test effort adequate? Could we have fit more testing in this release?
The Fundamental Metrics
As a tester, your road to metric creation has to start somewhere. Fundamental QA metrics are a combination of absolute numbers that can then be used to produce derivative metrics.
Absolute Numbers:
- Total number of test cases
- Number of test cases passed
- Number of test cases failed
- Number of test cases blocked
- Number of defects found
- Number of defects accepted
- Number of defects rejected
- Number of defects deferred
- Number of critical defects
- Number of planned test hours
- Number of actual test hours
- Number of bugs found after shipping"
