A Tour of NTL: NTL past, present, and future
Work on NTL started around 1990, when I wanted to implement some new algorithms for factoring polynomials over finite fields. I found that none of the available software was adequate for this task, mainly because the code for polynomial arithmetic in the available software was too slow. So I wrote my own. My starting point was Arjen Lenstra's LIP package for long integer arithmetic, which was written in C. It soon became clear that using C++ instead of C would be much more productive and less prone to errors, mainly because of C++'s constructors and destructors which allow memory management to be automated. Using C++ has other benefits as well, like function and operator overloading, which makes for more readable code.
One of the basic design principles of LIP was portability. I adopted this principle for NTL as well, for a number of reasons, not the least of which was that my computing environment kept changing whenever I changed jobs. Achieving portability is getting easier as standards, like IEEE floating point, get widely adopted, and as the definition of and implementations of the C++ language stabilize.
Since 1990, NTL has evolved in many ways, and it now provides a fairly polished and well-rounded programming interface.
When I started working on NTL, there really were not that many good, portable long integer packages around. Besides LIP, there was the BSD Unix MP library. The first version of GMP was released in the early 1990's. At that point in time, LIP seemed like the best starting point. LIP remains a reasonable long integer package, but in recent years, GMP has really become quite good: it seems well supported on many platforms, and is typically much faster than LIP.
I've now re-structured NTL so that one can use either 'traditional' LIP or GMP as the long integer package.
As you can well imagine, there is potentially no end to algorithms one could implement. That is why I have to stop somewhere. I think NTL has reached a point where it provides a reasonably well-rounded suite of algorithms for basic problems. I plan to continue supporting NTL, fixing bugs and improving performance.
While I don't have time to add significant new functionality to NTL, there seems to be an ever-growing number of NTL users out there, and I encourage them to make their code available to others. These might be in the form of NTL "add ons", but there is the possibility of integrating new functionality or algorithmic improvements into NTL itself.