Hot answers tagged data-driven
3
Nose supports parametric/generative tests, http://readthedocs.org/docs/nose/en/latest/writing_tests.html#test-generators
For example:
def checker(combination):
# do something to verify the combination
assert 'A' in combination
def test_generator():
options = ['A', 'B', 'C']
for o in options:
yield checker, o
for p in ...
2
There are lots of ways to do this; some of the data points I have used in the past are:
Build breakage: is the automated build compilation/test failure rate going up or down?
Assuming an Agile development model, are the user stories complete and have they been reviewed by QA + stakeholders
Has the code freeze been effective? Are developers still checking ...
1
If I understand you situation correctly you have a data-driven test, and you want to be able to run that data-driven test using the arguments in the 'datafile' against one or more services with varying locations.
One approach may be to read in a file that lists the desired services (location) at runtime into an array, then loop through each element ...
1
I don't think that there can be such a concept as an "acceptable" defect arrival rate, in the sense of a target number as you typically want to discover them as fast as possible. So, in english, you want to find as many bugs as you can.
The key way to read that metric is that you want a consistent arrival rate over time, i.e. you want the defect arrival ...
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