I am a particle physicist, and used to use ROOT every working day. It is still used daily by thousands of other particle physicists, though, and is a core part

I am a particle physicist, and used to use ROOT every working day. It is still used daily by thousands of other particle physicists, though, and is a core part of many high-energy physics experiments. I think there are a few of objectively neat features of ROOT: * Versioned persistency of C++ objects deriving from the TObject base class [1]; * Script-like execution of C++ and a C++ REPL based on clang [2]; and * Dynamic bindings of the C++ classes to Python [3]. There's an accompanying, but independently developed, file access protocol for reading and writing ROOT files over a network, too [4]. On the other (subjective) hand, ROOT is regarded a pain to use by ‘analysts’, the people who use ROOT to make the results that go in to physics papers. There are already some good, old-but-still-valid critiques [5, 6], so I won't say too much, but I think a large part of the problem comes from two things: 1. ROOT tries its best to do everything that a particle physicist might want to do. This encompasses a very wide range of things, and this has lead to ROOT having a very large, often intractable codebase that cannot be modularised. 2. It has failed to keep up with contemporary coding techniques and analysis methods. Most of the PhD students I know use the Python interface to ROOT, and yet the ROOT developers are planning to drop Python support for the next major version (ROOT 7, which is expected in 2018). Those that do use C++ aren't able to use even C++11 effectively with ROOT, as its interfaces aren't compatible. Luckily, I'm confident that analysts will move to a better way. I've been very encouraged by the astrophysics and machine learning communities in particular, who are using Python to do low- and high-level analysis on large datasets, as we do in particle physics, and are producing fantastic results. Tools like pandas, matplotlib, and scikit-learn are an absolute joy to use in comparison with ROOT, and the communities within the Python ecosystem are wonderful: they foster very open code development, and value readable, well-documented, fast code. I don't need ROOT to get any better, because I think the future is already here. [1]: https://root.cern.ch/root/html534/guides/users-guide/InputOutput.html#inputoutput https://root.cern.ch/root/html534/guides/users-guide/InputOu... [2]: https://root.cern.ch/cint-prompt https://root.cern.ch/cint-prompt [3]: https://root.cern.ch/pyroot https://root.cern.ch/pyroot [4]: http://xrootd.org http://xrootd.org [5]: http://www.insectnation.org/articles/problems-with-root.html http://www.insectnation.org/articles/problems-with-root.html [6]: http://www.insectnation.org/articles/root-wishlist.html http://www.insectnation.org/articles/root-wishlist.html