I'd say the problem is more from the academic side. If good data isn't available, then academics should not be publishing papers on toy data. It's meaningless. The goal is not to publish papers but to advance science.
While I tend to agree, the research we environment demands this nonsense. Also, they have to start somewhere to set a record to get future funding. Should probably do more survey studies of what data exists and where the state of things are then suggest new studies and seek funding for it.
Short of large and completely government funded development projects, I think it would be a struggle to get data. Few businesses would be willing to offer up development processes and surrounding data due to potential IP lost. Any organization that has good processes have it in their interest to striffle others from discovering how to improve theirs or learn from the success of others.
Part of the issue is that academia largely just doesn't pay for software development which they can leverage as an accessible cheap data source, it's done as a completely privatized exercise. Any research that requires highly protected commercial processes is pretty difficult to get any traction on unless you're inadvertently rediscovering the same processes (from my experience).
With that said, I feel like the amount of empirical data you'd need is going to be incredibly high, much if it not even currently being collected.
Research at business schools manage to find all types of data that companies believe is way more integral to their success than information about their software estimation process.
These researchers are choosing to waste their own time and governments money, because it's easier to play with new toy machine learning models than go to networking event and befriend software VPs in order to convince them to give you their data.
Rereading my comment I think you're right. Been frustrated with bureaucracy related to covid (specifically the vaccine) and the lives it's costing. And that frustration was redirected to other people following silly rules with far less at stake.
I still think a lot of research in software engineering is useless because researchers spend too much time focusing on different methods and not enough going out into the world to collect better data. And researchers should be mildly ashamed for doing crappy research.
But also my tone should have been more constructive.
Could not disagree more. The premise of this piece is that dieting is just willpower, beating addiction is the same, an entirely individual problem.
The reality is that the incentives are what society is asking for, with ethics etc acting as constraints only, rather than actively rewarded. In that formulation it is inevitable (and optimal) that some people will skate to the edge, and if the edge is poorly enforced they will increasingly go over.
Policies must address the overall actual effects, not just a chimerical ideal.
(It is even more ridiculous coming from someone in psychology.)
