Metrics needed to measure the quality of the product in Agile

One of the most important things in Software projects is measuring the quality of Software. Here are few metrics that we follow in our company and which plays an important role in measuring our software's quality.

Stories committed vs Stories delivered
The ability of teams to meet their commitments on schedule and with the highest standards. Failing to deliver at right time causes delays and rework.

Quality across sprints
QA doesn't have time and resources to test each and every build in sprint. So, one of the major metrics is automation within the sprint. The feature/story delivered in sprint should be automated in same sprint.

Defect Age (Bug cycle time)
It is known fact that the fixing code at one place affects other. Also, we have a famous saying that "A Stitch in-time saves nine". Fixing a bug in time saves many regression.

Defect Density
A straight forward metric to measure the defects that were introduced vs the new lines of code written. All kinds of defect metrics can be used to calculate defect rate of the product. A good defect
rate target should lead to a release-to-release reduction in the total number of defects.

Customer Satisfaction
It is a good practice to consider Customer's perspective. While fixing, there might be few defects which are not valid or major in our perspective like documentation and usability bugs. These increases customer problems.

Code Coverage
A good code coverage metrics is also a measure for the quality of the product.

Code Coverage – Measure the quality of your testing

Many of you (testing guys) may have already heard of code coverage and related tools. However, let’s talk about why do we need code coverage, how does it helps and when do we need to do code coverage analysis.

Code Coverage Analysis helps finding more bugs in our application code by finding the areas which are not being covered in our testing. It measures how many lines/blocks/arcs of our code are executed while the automated tests are running. And the coverage is collected by using specialized tools to instrument the binaries to add tracing calls and run a full set of automated tests against the instrumented product. A good tool will give us not only the percentage of the code that is executed, but also will allow us to drill into the data and see exactly which lines of code were executed/not executed during particular test which inturn gives us the test cases missing.

There are many tools available in market that can be used to indicate which code is being executed when running through test cases, for example in our company, we use Clover for all our Java based applications and Pure Coverage for C/C++ based applications. Code Coverage is a white box testing which can be executed mostly at testing phases like regression or integration testing.