Improve Code Coverage Metric

 I know, every body knows that Code Coverage is a weak metric (Link). But there are two ways to improve the value of he code coverage metrics:

1. Remove all exclusion pattern
2. Remove integration test from the calculation

Point 1 should avoids that you cheat your self.

Point 2 is not so obviously but it's easy to explain. Integration tests ensure that the whole software or larger parts work. Unit tests are the result of TDD and code coverage could measure the TDD impact. That's the reason why only unit tests should part of the code coverage calculation.

How to build stable and reliable System Test for Micro Services

Work in Progress, I'm currently overwork this article. Please come back later!

 

 

System tests are testing the orchestration of a bunch of micro services. Most of the test covers external features used by other micro services or by the front end.

If the current micro service is optimized for resilience (Yeah, Great) then system tests on feature endpoints can't discover errors related to (incoming) dependend micro services. The root cause of this lower power system test is the decoupling of micro services eg via the Fail Fast Pattern  or other Circuit Breakers (Thanks to Netflix). Or with other words resilience pattern could reduce the value of system tests.

System Tests improved by Diagnostic Endpoints

One way to avoid this negative side of resilience is to introduce what I called Diagnostic Endpoints. A diagnostic endpoint is only used by system test an not by features. The goal of diagnostic endpoints are to verify that functions that are covered eg by resilience pattern work.

In the real world, we save a huge amount of time after establishing of diagnostic endpoints. The software developers and the Project Owner love them.