The equivalence of folding left and right over Peano numbers and lists makes it possible to minimalistically inter-derive (1) structurally recursive functions in direct style, (2) structurally tail-recursive functions that use an accumulator, and (3) structurally tail-recursive functions in delimited continuation-passing style, using Ohori and Sasano’s lightweight fusion by fixed-point promotion. When the fold-left and the fold-right functions account for primitive iteration for Peano numbers, this equivalence is unconditional. When they account for primitive recursion for Peano numbers, this equivalence is modulo left permutativity of their induction-step parameter – a property which is more general than associativity and commutativity. And when they account for primitive iteration or for primitive recursion over lists, this equivalence is modulo left permutativity of their induction-step parameter if these two fold functions have the same type. Since the 1980s, however, the two fold functions for lists do not have the same type: the arguments for their induction-step parameter are swapped, a re-ordering that complicated Bird and Wadler’s duality theorems and whose history is reviewed in an appendix. Without this re-ordering, Bird and Wadler’s second duality theorem more visibly accounts for “re-bracketing,” which is a key step to make recursive programs tail recursive in the general area of program development, from Cooper in the 1960s and onwards.

The Garsia–Wachs algorithm is an algorithm for building a binary leaf tree whose cost is as small as possible. The problem and the algorithm are described in more detail below, but the task is essentially the same as that of building a Huffman coding tree with the added constraint that the fringe of the tree has to be exactly the given list of inputs (in Huffman coding, the fringe of the tree can be any permutation of the input). As we will show below, the Garsia–Wachs algorithm can be implemented with a linearithmic running time—a running time of O (n log n) steps for an input of length n, the same time bound as for Huffman coding.

The Knuth–Morris–Pratt (KMP) algorithm for string search is notoriously difficult to understand. Lost in a sea of index arithmetic, most explanations of KMP obscure its essence. This paper constructs KMP incrementally, using pictures to illustrate each step. The end result is easier to comprehend. Additionally, the derivation uses only elementary functional programming techniques.

The setting is a class on functional programming. There are four students: Anne, Jack, Mary and Theo.

From the outset, lambda calculus represented natural numbers through iterated application. The successor hence adds one more application, and the predecessor removes. In effect, the predecessor un-applies a term—which seemed impossible, even to Church. It took Kleene a rather oblique glance to sight a related representation of numbers, with an easier predecessor. Let us see what we can do if we look at this old problem with today’s eyes. We discern the systematic ways to derive more predecessors—smaller, faster, and sharper—while keeping all teeth.

Vectors—or length-indexed lists—are classic example of a dependent type. Yet, most tutorials stay clear of any function on vectors whose definition requires non-trivial equalities between natural numbers to type check. This pearl shows how to write functions, such as vector reverse, that rely on monoidal equalities to be type correct without having to write any additional proofs. These techniques can be applied to many other functions over types indexed by a monoid, written using an accumulating parameter, and even be used to decide arbitrary equalities over monoids ‘for free.’

This pearl defines a translation from well-typed lambda terms to combinatory logic, where both the preservation of types and the correctness of the translation are enforced statically.

The other day, I was assembling lecture material for a course on Agda. Pursuing an application-driven approach, I was looking for correctness proofs of popular algorithms. One of my all-time favourites is Huffman data compression (Huffman, 1952). Even though it is probably safe to assume that you are familiar with this algorithmic gem, a brief reminder of the essential idea may not be amiss.

Let’s say we want to create the two charts in Figure 1. The chart on the left is a bar chart that shows two different values for each bar. The chart on the right consists of two line charts that share the x axis with parts of the timeline highlighted using two different colors.

Comparison networks offer an attractive framework for studying parallel sorting algorithms. The visual presentation of such hard-wired networks makes processes easy to conceptualize without the overhead of programming syntax or the semantic complications of concurrency. Though simple in appearance they have a surprisingly rich structure. In this pearl we delve a little into their theory.

We consider the task of constructing 2-3 trees. Given a sequence of elements we seek to build a 2-3 tree–in linear time–that contains the elements in symmetric order. We discuss three approaches: top-down, bottom-up, and incremental. The incremental approach is more flexible than the other two in that it allows us to interleave the construction work with other operations, for example, queries.

Consider the following puzzle: given a number, remove k digits such that the resulting number is as large as possible. Various techniques are employed to derive a linear-time solution to the puzzle: we justify the structure of a greedy algorithm by predicate logic, give a constructive proof of the greedy condition using a dependently typed proof assistant and calculate the greedy step as well as the final, linear-time optimisation by equational reasoning.

Given a string of parentheses, the task is to find the longest consecutive segment that is balanced, in linear time. We find this problem interesting because it involves a combination of techniques: the usual approach for solving segment problems and a theorem for constructing the inverse of a function—through which we derive an instance of shift-reduce parsing.

Haskell (Peyton Jones, 2003) is often used as a host language for embedding other languages. Typically, the abstract syntax of the guest language is defined by a collection of datatype declarations; parsers and pretty-printers convert between the concrete syntax and its abstract representation. A quote/antiquote mechanism permits a tighter integration of the guest language into the host language by allowing one to use phrases in the guest language's concrete syntax.

Okasaki introduced the canonical formulation of functional red-black trees when he gave a concise, elegant method of persistent element insertion. Persistent element deletion, on the other hand, has not enjoyed the same treatment. For this reason, many functional implementations simply omit persistent deletion. Those that include deletion typically take one of two approaches. The more-common approach is a superficial translation of the standard imperative algorithm. The resulting algorithm has functional airs but remains clumsy and verbose, characteristic of its imperative heritage. (Indeed, even the term insertion is a holdover from imperative origins, but is now established in functional contexts. Accordingly, we use the term deletion which has the same connotation.) The less-common approach leverages the features of advanced type systems, which obscures the essence of the algorithm. Nevertheless, foreign-language implementors reference such implementations and, apparently unable to tease apart the algorithm and its type specification, transliterate the entirety unnecessarily. Our goal is to provide for persistent deletion what Okasaki did for insertion: a succinct, comprehensible method that will liberate implementors. We conceptually simplify deletion by temporarily introducing a “double-black” color into Okasaki's tree type. This third color, with its natural interpretation, significantly simplifies the preservation of invariants during deletion.