>> A new static analysis is likely to be far too compute-intensive to be offered to the public on hardware the research group has the time/money to operate. Le

>> A new static analysis is likely to be far too compute-intensive to be offered to the public on hardware the research group has the time/money to operate. Let's describe the division between Academics and users: Academics get a cloud based service platform, where academics install the software which is usable by API/library[1] calls , automatically(or manually by users) scalable , with automatic billing where X percent goes to academics. If you're a user you can also use the platform to build your own software , you can easily call the academic's API/library , and you both can share databases and file-systems. I can even see possibility to require that academic and user code reside on the same machine on a different VM's when disk access speed is critical. I can imagine this working in the static analysis example, and plenty other examples, just enter "python library" into google scholar, half the stuff there look usable in this form on first look. The trick would be of course to make it so easy for a academic to share his code in this form , so that this would be the default way of working. Than we'll get some interesting stuff, some of it production systems and some of it just prototypes. But even if we are talking about tons of amazing prototypes , i see plenty of value. Does it all make sense? [1]There are some ways of doing RPC , that are really easy to use, almost library like.