When a C programmer needs an efficient data structure for a particular problem, he or she can often simply look one up in any of a number of good textbooks or handbooks. Unfortunately, programmers in functional languages such as Standard ML or Haskell do not have this luxury. Although most of these books purport to be language-independent, they are unfortunately language-independent only in the sense of Henry Ford: Programmers can use any language they want, as long as it's imperative. To rectify this imbalance, this book describes data structures from a functional point of view. We use Standard ML for all our examples, but the programs are easily translated into other functional languages such as Haskell or Lisp. We include Haskell versions of our programs in Appendix A.

Functional vs. Imperative Data Structures

The methodological benefits of functional languages are well known [Bac78, Hug89, HJ94], but still the vast majority of programs are written in imperative languages such as C. This apparent contradiction is easily explained by the fact that functional languages have historically been slower than their more traditional cousins, but this gap is narrowing. Impressive advances have been made across a wide front, from basic compiler technology to sophisticated analyses and optimizations.