Can somebody please shine some light on why such an endeavor was undertaken by CERN? What was so important about JIT C++ that they had to write such a sophisticated piece of software?
We had a "C++ interpreter" called CINT for a long time, which the ROOT data analysis framework was built around. It was, to put it bluntly, a mess: it had inconsistent scoping and syntax with C++, gave worthless debugging messages, and couldn't handle a lot of standard C++ code.
It was also the way that a lot of physicists at CERN ran their analysis code. We needed an interactive language to make graphs and histograms and to fit our data, and when CINT was conceived the only other solutions were proprietary packages like MATLAB. So CERN went with a homegrown solution and wrote a C++ interpreter many years ago.
Flash forward 15 years. "Big data" is all the rage. Python, R, and the huge list of packages built around around them would easily solve the problems CINT was designed for. But the codebase for the larger experiments at CERN is maintained by physics graduate students, a good fraction of whom had no programming experience before grad school. We don't have the time or the resources to rewrite our existing code in scipy, and the older generation doesn't have the experience to supervise such a transition.
Given that so many physicists are still using CINT, the ROOT developers had to make a choice: they could continue to maintain CINT, which would have been nearly impossible with their resources and the evolution of C++, or they could rewrite something that did almost the same thing using more modern tools. They opted for the later.
cint (M. G.) was in maintenance-mode for a long time by then.
ph-sft group was more for python (P. M.), and fnal wanted llvm/c++ (P.C.).
fnal then put down the money for an IC contract (A.N.) at ph-sft for the llvm/c++ based implementation and joined the iso body.
cling is almost orthogonal to the whole ROOT mess (graphics, histogramming, partially the analysis etc.)
Actually there was an early attempt to provide C++ repls back in the early 90's with Lucid Energize C++, after they pivoted from Lisp Machines and applied their knowledge to C++.
https://www.youtube.com/watch?v=pQQTScuApWk
Also the majority of CERN code is written in a mix of Fortran and C++, and not all teams like to use Python. So they rather use something that provides interactivity to research their algorithms and speed at the same time.
Now imagine if that was the standard way everyone worked by now.