I agree generally with data and code sharing policies (all of my recent papers include zenodo deposits of data, and I work on a large open source simulation code). However, there are some serious issues here:
1. Code licensing is not always clear. Sometimes you are working with a code that some PhD student wrote, who left the field, whose advisor shared it with you. Can you share this code? Not necessarily... but this problem will go away with time.
2. Some codes include proprietary components, and chopping them out can make the code inoperable (or useless). One notable instance of this is a very famous hydro code that was used to produce predictions for nukes, that was then repurposed for running simulations of planetary collisions.
3. Sharing data is prohibitive, and if you don't have the data having the code might not really help. Our projects can produce Pbs of data, costing 10s-100s Ms of CPU hours, and as such making the data open source can be really tricky. This then means you can only share a selection of runs. On the other hand, even if you had the code, you can't reproduce a lot of the results, because of the cost of running the simulations... This actually will get _worse_ over time as we run bigger and bigger simulations.