On the contrary; in that case there are four possibilities:
a: your algorithm doesn't work at all, and your observations are a artifact of convenient inputs or inept measurements.
b: your algorithm works, but the description in the paper is wrong or incomplete
c: your algorithm works as described, but the replicater implemented it incorrectly
d: other
Having the original implementation code is necessary to distinguish between cases a and b versus case c, and if the former, the code for the test harness is likely to help distinguish a versus b. (Case d is of course still a problem, but that doesn't mean it's reasonable to just give up.)
I'm all for more transparency, and this includes making codes and data public as much as is reasonable. But the real test is if someone can independently replicate the result, and how to incentivize replication studies (in both computational and experimental science) is also important, and in my view should not be divorced from discussions of reproducibility.
Edit: rewrote to clarify my position.
Edit: more careful phrasing.