chemf: A purely functional chemistry toolkit by Stefan Höck and Rainer Riedl. (Journal of Cheminformatics 2012, 4:38 doi:10.1186/1758-2946-4-38)
Abstract:
Background
Although programming in a type-safe and referentially transparent style offers several advantages over working with mutable data structures and side effects, this style of programming has not seen much use in chemistry-related software. Since functional programming languages were designed with referential transparency in mind, these languages offer a lot of support when writing immutable data structures and side-effects free code. We therefore started implementing our own toolkit based on the above programming paradigms in a modern, versatile programming language.
Results
We present our initial results with functional programming in chemistry by first describing an immutable data structure for molecular graphs together with a couple of simple algorithms to calculate basic molecular properties before writing a complete SMILES parser in accordance with the OpenSMILES specification. Along the way we show how to deal with input validation, error handling, bulk operations, and parallelization in a purely functional way. At the end we also analyze and improve our algorithms and data structures in terms of performance and compare it to existing toolkits both object-oriented and purely functional. All code was written in Scala, a modern multi-paradigm programming language with a strong support for functional programming and a highly sophisticated type system.
Conclusions
We have successfully made the first important steps towards a purely functional chemistry toolkit. The data structures and algorithms presented in this article perform well while at the same time they can be safely used in parallelized applications, such as computer aided drug design experiments, without further adjustments. This stands in contrast to existing object-oriented toolkits where thread safety of data structures and algorithms is a deliberate design decision that can be hard to implement. Finally, the level of type-safety achieved by \emph{Scala} highly increased the reliability of our code as well as the productivity of the programmers involved in this project.
Another vote in favor of functional programming as a path to parallel processing.
Can the next step, identity transparency*, be far behind?
*Identity transparency: where any identification of an entity can be replaced with another identification of the same entity.