DevX interviewed Bjarne Stroustrup about C++0x, the new C++ standard that is due in 2009. Bjarne Stroustrup has classified the new features into three categories Concurrency, Libraries and Language. The changes introduced in the Concurrency makes C++ more standardized and easy to use on multi-core processors. It is good to see that some of the commonly used libraries are becoming standard (eg: unordered_maps and regex).
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Additionally, C++ is an excellent language to write code where you need performance and tie it up with Python code (or your favorite dynamic language ). E.g. Boost.Python is excellent for creating Python bindings for C++ code.
The problem is that it is so slow to compiler anything non trivial with boost.Python that is it is painful to develop with. I agree that in theory, it is nice, but I find it quite unusable in practice.
I personally believe the trend is toward doing as much as possible in scripting language, with some compiled code where needed, and moving away from scripting something which is essentially C++. Some core things (basic toolkits, etc...) will still be written in compiled languages for quite some time of course, but environments like python for scientific programming give you much more flexibility that what you can get by just wrapping a huge, inflexible C++ framework. Prototyping speed is a key factor, both in academic and in the private markets (finance, data analysis, etc...), and C++ is just so much behind for this that is cannot compete, even with top notch programmers.
Member since:
2005-11-11
The problem is that it is so slow to compiler anything non trivial with boost.Python that is it is painful to develop with. I agree that in theory, it is nice, but I find it quite unusable in practice.
I personally believe the trend is toward doing as much as possible in scripting language, with some compiled code where needed, and moving away from scripting something which is essentially C++. Some core things (basic toolkits, etc...) will still be written in compiled languages for quite some time of course, but environments like python for scientific programming give you much more flexibility that what you can get by just wrapping a huge, inflexible C++ framework. Prototyping speed is a key factor, both in academic and in the private markets (finance, data analysis, etc...), and C++ is just so much behind for this that is cannot compete, even with top notch programmers.