• instability estimate of full-stack tests.
  • identify acceptance tests
  • testing pyramid
    • cost of a test
  • testing feedback loop


  • as many unit tests as possible
  • as few integration tests and full-stack tests as possible
  • code coverage isn't a perfect metric of defect detection. Test count is better.

The Details

What do we want from tests?

The most valuable tests provide the most coverage for the smallest developer cost.

as of 2016, hardware is relatively cheap (ELABORATE)

Fast Feedback


Working Backwards (MTTR, MTBF, MTTD)

It's often the case to examine testing as a problem in isolation, but starting with the goal, as with product design, helps testing as well.

A successful testing process is one that helps reliability of the product(s) provided by your team. Using the common KPIs for SRE's works great as KPIs here:

  • MTBF (Mean Time Between Failure): mean time between issues in production
  • MTTR (Mean Time To Recovery): time to recover from an issue, once discovered
  • MTTD (Mean Time To Detection): time to find that an issue exists

How does testing affect these KPIS?


If bugs are caught before they are shipped, then that is a failure that does not ship to production. Assume that all regressions come in at some frequency N. If we increase the likelyhood of finding bugs in test by 10%, then or frequency reduces to 0.9N.

MTBF = 1 / N. So assuming that N = 10 regressions / 30 days, decreasing that to 9 results in:

MTBF_OLD = 1 / (30 days / 10 regressions) = 3 days
MTBF_NEW = 1 / (30 days / 9 regressions) = 3.3 days


Mean time to recovery is helped with more granular monitors, as the root cause becomes quicker to detect.


Mean time to detect is helped with more monitoring, as the root cause is discovered quickly.

Measuring MTBF, and acceptance tests

So with MTBF defined, what is a failure? Choose the definition you prefer, but a simple one would be "failure occurs when an acceptance criteria is no longer satisfied". Basically, if the end consumer has their core experience degraded significantly.

To measure and detect this failure, acceptance tests, and monitors evaluating if acceptance criteria is satisfield, are needed.

Thus, there should be an acceptance test and/or monitor for every core use case.

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