iteration1_manual (/65): All of the non-automarking
marks that your tutor awarded you
Your tutor has already given you feedback for these
non-automarking parts, but if you have further
questions you can direct those questions to them in
the week 7 project check-in
iteration1_auto_own_tests (/5):
Full marks if you passed all your own pytests (easy
marks!!)
These are basically free marks since nearly all
groups submitted pytests that passed their own code.
Your mark is determined by how many of your own
pytests you passed (passing all = 5/5)
iteration1_auto_course_tests (/30):
We ran OUR tests against YOUR implementation to see
how you performed
We wrote a series of tests and then ran them against
your implementation.
We wrote 35 marks worth of tests, but capped this
mark at 30. So basically scoring 30/35 in this
section gave you the full marks.
For the two automarking marks:
If you want to see the results of the automarker, you
can checkout a branch I pushed to your repo called "
iter1-results
". This contains two text files:
results_own.txt - the result of the pytests when we
ran YOUR tests against your implementation
results_course.txt - the result of the pytests when
we ran OUR tests against your implement
We can't give you the source code for the tests,
otherwise we'd basically be giving you assignment
solutions. You'll have to interpret the pytest
output as best you can, and you can talk to your
tutor in week 7 if you need their help.
If you have discovered a minor error in your iteration 1
code that you think could drastically improve your mark
(e.g. bad imports), then make a new branch off your
iteration 1 branch called "iter1-fix" and make the fixes
on that branch. During the week 7 project check-in share
this branch with your tutor so they can re-run the
automarker to see if you gain the extra marks
Note: For every unique change you make to your code,
we will remove 1/3 of the marks off your new
automark result - so please don't waste time trying
to make tiny tweaks to your code to gain a mark or
two. Just learn from your mistakes! :)
Resource created
Saturday 20 March 2021, 02:09:05 AM, last modified
Saturday 20 March 2021, 04:05:07 PM.