An object encoding translates a language with object primitives to one without. Similarly, a class encoding translates classes into other primitives. Both are important theoretically for comparing the expressive power of languages and for transferring results from traditional languages to those with objects and classes. Both are also important foundations for the implementation of object-oriented languages as compilers typically include a phase that performs these translations. This paper describes a language with a primitive notion of classes and objects and presents an encoding of this language into one with records and functions. The encoding uses two techniques often used in compilers for single-inheritance class-based object-oriented languages: the self-application semantics and the method-table technique. To type the output of the encoding, the encoding uses a new formulation of self quantifiers that is more powerful than previous approaches.

Expressing algorithms using immutable arrays greatly simplifies the challenges of automatic SIMD vectorization, since several important classes of dependency violations cannot occur. The Haskell programming language provides libraries for programming with immutable arrays, and compiler support for optimizing them to eliminate the overhead of intermediate temporary arrays. We describe an implementation of automatic SIMD vectorization in a Haskell compiler which gives substantial vector speedups for a range of programs written in a natural programming style. We compare performance with that of programs compiled by the Glasgow Haskell Compiler.