[jgamman]

i can't see a business model - the scientist is already paying with their time to get something working that is just good enough for publication. all the problems you describe are down the road and scientists kick that to 'industry'. unless your 'right way' is also easier to boot, why would they add to their time?

[Thriptic]

I think that is indeed the perception, but that the time savings would actually be quite pronounced if people did things correctly. I've seen many projects get immediately bogged down by bugs / feature creep / lack of planning and end up taking far longer than if people had done things correctly. Also, many labs hand off code bases when post docs or students leave, creating chaos for the next person that is tasked with working on them.

As an example, I wrote a proof of concept script to show that we could automate some basic image analysis in my lab three years ago. That was immediately grabbed by an investigator and put into production without any further thought. Because it was a proof of concept script, it was of course very buggy and required substantial feature addition. This was added without any thought for design etc. Fast forward to today and this code base is a sprawling shit show which is being rewritten for the THIRD TIME. Each time has ended in failure because people failed to observe basic best practice, and this attempt will likely fail too. That is an ENORMOUS waste of investigator time. Another project I can think of involved a model which had a 10,000 line function. No one could trust what was being outputted by the thing, so they eventually abandoned it. That's hundreds of investigator hours down the drain.