The code should be published, and knowing this, researchers will hopefully try avoid certain commonly harmful practices. One of these is re-using the same scrip

The code should be published, and knowing this, researchers will hopefully try avoid certain commonly harmful practices. One of these is re-using the same script to run slightly different models by editing some of the hard-coded parameters. I've myself found more than one mistake in someone else's reported results due to this sort of thing. But identifying it was quite a bit of trouble because the record of what was ran was erased when they moved on to the next model. What I would not expect from people is code that would necessarily run in your environment. For example, in many cases, the paths are going to be hard-coded, for a variety of reasons. It might be ideal to write code that will just work, in a reproducible environment, but that often takes more work than people are willing to commit to, given all the other things they have to do. Finally, cleaning up your code for presentation is a final opportunity for you to discover any mistakes before you publish and then later have an embarrassing public retraction.