The Java phenomenon means that programmers that once laughed at garbage collection and strong typing have started to use it daily, and this opens up a wonderful opportunity for the functional programming community.

Bob Harper coined the acronym HOT to summarise much of what functional programmers have to offer the world: expertise in languages that are Higher-Order and Typed. Bob argued for a broad interpretation of these terms, so that Higher-Order includes languages where objects contain methods (even though functions are not first-class citizens), and Typed includes both static and dynamic typing. By these criteria Java is HOT, and so are Haskell, ML and Scheme.

We present narrowing calculi that are computation models of functional-logic programming languages. The narrowing calculi are based on the notion of the leftmost outside-in reduction of Huet and Lévy. We note the correspondence between the narrowing and reduction derivations, and define the leftmost outside-in narrowing derivation. We then give a narrowing calculus OINC that generates the leftmost outside-in narrowing derivations. It consists of several inference rules that perform the leftmost outside-in narrowing. We prove the completeness of OINC using an ordering defined over a narrowing derivation space. To use the calculus OINC as a model of computation of functional-logic programming, we extend OINC to incorporate strict equality. The extension results in a new narrowing calculus, s-OINC. We show also that s-OINC enjoys the same completeness property as OINC.

NATURAL EXPERT is a product that allows users to build knowledge-based systems. It uses a lazy functional language, NATURAL EXPERT LANGUAGE, to implement backward chaining and provide a reliable knowledge processing environment in which development can take place. Customers from all over the world buy the system and have used it to handle a variety of problems, including applications such as airplane servicing and bank loan assessment. Some of these are used 10,000 times or more per month.

This paper describes EQUALS, a fast parallel implementation of a lazy functional language on a commercially available shared-memory parallel machine, the Sequent Symmetry. In contrast to previous implementations, we propagate normal form demand at compile time as well as run time, and detect parallelism automatically using strictness analysis. The EQUALS implementation indicates the effectiveness of NF-demand propagation in identifying significant parallelism and in achieving good sequential as well as parallel performance. Another important difference between EQUALS and previous implementations is the use of reference counting for memory management, instead of mark-and-sweep or copying garbage collection. Implementation results show that reference counting leads to very good scalability and low memory requirements, and offers sequential performance comparable to generational garbage collectors. We compare the performance of EQUALS with that of other parallel implementations (the 〈v, G〉-machine and GAML) as well as with the performance of SML/NJ, a sequential implementation of a strict language.

The popular method of enumerating the primes is the Sieve of Eratosthenes. It can be programmed very neatly in a lazy functional language, but runs rather slowly. A little-known alternative method is the Wheel Sieve, originally formulated as a fast imperative algorithm for obtaining all primes up to a given limit, assuming destructive access to a bit-array. This article describes functional variants of the wheel sieve that enumerate all primes as a lazy list.