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'I have a pen' got him full marks on the unit test.
Figure 2 K -means clustering – Distribution of the C V of the unit test case metrics.
Here also the first component captures all dimensions measured by the unit test case metrics.
So, the first component captures all dimensions measured by the unit test case metrics.
Moreover, all the unit test case metrics are closed and highly correlated to component F1.
Figure 1 K -means clustering – Distribution of the mean values of the unit test case metrics.
The values of the unit test case metrics have been computed using the tool we developed.
Table 11 gives the descriptive statistics (total of observations) of the unit test case metrics.
Usually, they are used to isolate the unit test from other classes.
We can then reasonably conclude that the unit test case metrics TINVOK and TLOC are the unit test case metrics that are the least sensitive to the changes in the style of test code writing.
This is also true for the standard deviation of the unit test case metrics, here also except for cluster 4 and this for all the unit test case metrics.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com