Datatype-generic programming is defining functions that depend on the structure, or “shape”, of datatypes. It has been around for more than 10 years, and a lot of progress has been made, in particular in the lazy functional programming language Haskell. There are more than 10 proposals for generic programming libraries or language extensions for Haskell. To compare and characterize the many generic programming libraries in a typed functional language, we introduce a set of criteria and develop a generic programming benchmark: a set of characteristic examples testing various facets of datatype-generic programming. We have implemented the benchmark for nine existing Haskell generic programming libraries and present the evaluation of the libraries. The comparison is useful for reaching a common standard for generic programming, but also for a programmer who has to choose a particular approach for datatype-generic programming.

Higher-order abstract syntax provides a convenient way of embedding domain-specific languages, but is awkward to analyse and manipulate directly. We explore the boundaries of higher-order abstract syntax. Our key tool is the unembedding of embedded terms as de Bruijn terms, enabling intensional analysis. As part of our solution we present techniques for separating the definition of an embedded program from its interpretation, giving modular extensions of the embedded language, and different ways to encode the types of the embedded language.

Datatype-generic programming involves parametrization by the shape of data, in the form of type constructors such as ‘list of’. Most approaches to datatype-generic programming are developed in the lazy functional programming language Haskell. We argue that the functional object-oriented language Scala is in many ways a better setting. Not only does Scala provide equivalents of all the necessary functional programming features (such parametric polymorphism, higher-order functions, higher-kinded type operations, and type- and constructor-classes), but it also provides the most useful features of object-oriented languages (such as subtyping, overriding, traditional single inheritance, and multiple inheritance in the form of traits). We show how this combination of features benefits datatype-generic programming, using three different approaches as illustrations.

The UNIX diff program finds the difference between two text files using a classic algorithm for determining the longest common subsequence; however, when working with structured input (e.g. program code), we often want to find the difference between tree-like data (e.g. the abstract syntax tree). In a functional programming language such as Haskell, we can represent this data with a family of (mutually recursive) datatypes. In this paper, we describe a functional, datatype-generic implementation of diff (and the associated program patch). Our approach requires advanced type system features to preserve type safety; therefore, we present the code in Agda, a dependently-typed language well-suited to datatypegeneric programming. In order to establish the usefulness of our work, we show that its efficiency can be improved with memoization and that it can also be defined in Haskell.

Aspect-Oriented Programming (AOP) aims at modularising crosscutting concerns that show up in software. The success of AOP has been almost viral and nearly all areas in Software Engineering and Programming Languages have become “infected ” by the AOP bug in one way or another. Interestingly the functional programming community (and, in particular, the pure functional programming community) seems to be resistant to the pandemic. The goal of this paper is to debate the possible causes of the functional programming community’s resistance and to raise awareness and interest by showcasing the benefits that could be gained from having a functional AOP language. At the same time, we identify the main challenges and explore the possible design-space. Categories and Subject Descriptors D.3.2 [Programming Languages]: Language Classifications—Applicative (functional) languages,

Datatype-generic programming increases program reliability by reducing code duplication and enhancing reusability and modularity. Several generic programming libraries for Haskell have been developed in the past few years. These libraries have been compared in detail with respect to expressiveness, extensibility, typing issues, etc., but performance comparisons have been brief, limited, and preliminary. It is widely believed that generic programs run slower than hand-written code. In this paper we present an extensive benchmarking suite for generic functions and analyze the potential for automatic code optimization at compilation time. Our benchmark confirms that generic programs, when compiled with the standard optimization flags of the Glasgow Haskell Compiler, are substantially slower than their hand-written counterparts. However, we also find that more advanced optimization capabilities of GHC can be used to further optimize generic functions, sometimes achieving the same efficiency as hand-written code. D.1.1 [Programming Tech-

Abstract. These lecture notes introduce libraries for datatype-generic programming in Haskell. We introduce three characteristic generic programming libraries: lightweight implementation of generics and dynamics, extensible and modular generics for the masses, and scrap your boilerplate. We show how to use them to use and write generic programs. In the case studies for the different libraries we introduce generic components of a medium-sized application which assists a student in solving mathematical exercises. 1

Datatype-generic programming increases program reliability by reducing code duplication and enhancing reusability and modularity. Several generic programming libraries for Haskell have been developed in the past few years. These libraries have been compared in detail with respect to expressiveness, extensibility, typing issues, etc., but performance comparisons have been brief, limited, and preliminary. It is widely believed that generic programs run slower than hand-written code. In this paper we present an extensive benchmark suite for generic functions and analyze the potential for automatic code optimization at compilation time. Our benchmark confirms that generic programs, when compiled with the standard optimization flags of the Glasgow Haskell Compiler (GHC), are substantially slower than their hand-written counterparts. However, we also find that more advanced optimization capabilities of GHC can be used to further optimize generic functions, sometimes achieving the same efficiency as hand-written code.

Higher-order abstract syntax provides a convenient way of embedding domain-specific languages, but is awkward to analyse and manipulate directly. We explore the boundaries of higher-order abstract syntax. Our key tool is the unembedding of embedded terms as de Bruijn terms, enabling intensional analysis. As part of our solution we present techniques for separating the definition of an embedded program from its interpretation, giving modular extensions of the embedded language, and different ways to encode the types of the embedded language.

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