I've been playing with the maths library, Breeze (a good introduction is here). It's written in Scala and uses a cunning stunt to avoid boilerplate code.
The problem with writing an efficient library in Java is autoboxing is horribly inefficient for sufficiently complicated mathematical operations. The solution is typically to make the code less generic and use primitives (as I did in my pet project, jMathematics).
Scala has a neat trick to avoid this. It uses the @specialized annotation. So, one of Breeze's implementations of a matrix looks like this:
final class DenseMatrix[@specialized(Int, Float, Double) V](...
val data: Array[V],
...)
This results in the compiler creating methods that use these 3 primitives as well as the more generic types. This leads to quite a lot of classes:
henryp@phillsdell:~/Code/Scala/Maths/breeze$ find ./target/scala-2.10/classes/ -name DenseMatrix* | wc -l
350
def valueAt(row: Int, col: Int) = apply(row,col)
henryp@phillsdell:~/Code/Scala/Maths/breeze$ for FILE in `find ./target/scala-2.10/classes/ -name DenseMatrix*` ; do { javap "$FILE" | grep "valueAt(int, int" ; } done
public int valueAt(int, int);
public java.lang.Object valueAt(int, int);
public float valueAt(int, int);
public java.lang.Object valueAt(int, int);
public double valueAt(int, int);
public java.lang.Object valueAt(int, int);
public V valueAt(int, int);
Great, so a generic Object return value plus methods for our three specialized primitives. What could possibly go wrong? Well careless use can lead to literally megabytes of code being generated. That's why it's so rare in the standard Scala libraries.
However, this is a big win for mathematics library writers.