Back to Math: Functional Programming

In his 1977 ACM Turing Award Lecture, John Backus identified the word-at-a-time style of programming, inherited from the underlying hardware and dubbed the "von Neumann bottleneck", as a major obstacle to the advancement of programming. In this keynote, I argue that the functional programming he advocated introduced its own bottleneck: that everything produced by a computation (including nothing) must be encoded as a single value. This "obligation to singularity" is foreign to modelling, where single values sit collegially between no values and two values. Exploring diverse examples, I will argue that adopting a modelling (de facto: relational) style of programming eliminates the functional bottleneck, and with it many of the data-to-control flow escapes that Backus originally sought to avoid.

Abstract. At a fundamental level, functional and object-oriented programming languages are all ‘higher-order’, in the sense that they support computing with values that are themselves pieces of program code encapsulated with a local environment. In functional languages these ‘active’ values are functions, while in object-oriented languages they are objects. Both styles of higher-order language claim to provide good support for writing adaptable programs, but functional and object-oriented languages achieve this adaptability in different ways: functional programs rely on parameterisation at the value, type and module level, while object-oriented languages rely primarily on subtyping and implementation inheritance. Here we compare these two approaches, mainly in terms of the features and properties of their type systems, and consider the benefits and disadvantages of unifying (or merging) the two paradigms by adding object-oriented features to ML as a base language. We argue that while some of the simpler aspects of object-oriented languages are compatible with ML, adding a full- edged class-based object system to ML leads to an excessively complex type system and relatively little expressive gain, especially if we aim to preserve that mostly functional style of programming that is a major advantage of ML.

In functional logic programs, rules are applicable independently of textual order, i.e., any rule can potentially be used to evaluate an expression. This is similar to logic languages and contrary to functional languages, e.g., Haskell enforces a strict sequential interpretation of rules. However, in some situations it is convenient to express alternatives by means of compact default rules. Although default rules are often used in functional programs, the non-deterministic nature of functional logic programs does not allow to directly transfer this concept from functional to functional logic languages in a meaningful way. In this paper we propose a new concept of default rules for Curry that supports a programming style similar to functional programming while preserving the core properties of functional logic programming, i.e., completeness, non-determinism, and logic-oriented uses of functions. We discuss the basic concept and sketch an initial implementation of it which exploits advanced features of functional logic languages.

In functional logic programs, rules are applicable independently of textual order, i.e., any rule can potentially be used to evaluate an expression. This is similar to logic languages and contrary to functional languages, e.g., Haskell enforces a strict sequential interpretation of rules. However, in some situations it is convenient to express alternatives by means of compact default rules. Although default rules are often used in functional programs, the non-deterministic nature of functional logic programs does not allow to directly transfer this concept from functional to functional logic languages in a meaningful way. In this paper, we propose a new concept of default rules for Curry that supports a programming style similar to functional programming while preserving the core properties of functional logic programming, i.e., completeness, non-determinism, and logic-oriented use of functions. We discuss the basic concept and propose an implementation which exploits advanced features of functional logic languages.

Polytypic Programming in Maude

Typing rule-based transformations over topological collections

article Free Access Share on Values and objects in programming languages Author: B. J. MacLennan Naval Postgraduate School, Monterey, CA Naval Postgraduate School, Monterey, CAView Profile Authors Info & Claims ACM SIGPLAN NoticesVolume 17Issue 12December 1982 pp 70–79https://doi.org/10.1145/988164.988172Online:01 December 1982Publication History 43citation121DownloadsMetricsTotal Citations43Total Downloads121Last 12 Months27Last 6 weeks14 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF

SummaryThe C programming language is a foundational technology for modern computing with millions of lines of code implementing everything from hobby projects to commercial operating systems. This installation base and the programmers producing it represent a massive software engineering investment spanning decades and likely to continue for decades more. Nevertheless, C, which was first standardized almost 30 years ago, lacks many features that make programming in more modern languages safer and more productive. The goal of the C project (pronounced “C for all”) is to create an extension of C that provides modern safety and productivity features while still ensuring strong backward compatibility with C and its programmers. Prior projects have attempted similar goals but failed to honor the C programming style; for instance, adding object‐oriented or functional programming with garbage collection is a nonstarter for many C developers. Specifically, C is designed to have an orthogonal feature set based closely on the C programming paradigm, so that C features can be added incrementally to existing C code bases, and C programmers can learn C extensions on an as‐needed basis, preserving investment in existing code and programmers. This paper presents a quick tour of C features, showing how their design avoids shortcomings of similar features in C and other C‐like languages. Experimental results are presented to validate several of the new features.

This research aims to fully integrate logic programming into the programming language Scheme. We use a minimalist approach, based on the observation that the fundamental aspects of logic programming, nondeterminism and unification, are separable both in concept and in implementation. We have found that only two new primitive functions and one new special form need to be added to Scheme to achieve this integration. Using these primitives, we can write programs in the style of Scheme, Icon, Prolog, or any mixture thereof. We have found that a style of programming that uses both logical and functional techniques can be more powerful than the use of either technique alone. Because Scheme has side effects and continuations, this research addresses different problems and choices than previous research [2, 16, 19] on merging functional and logical languages.

We explore the design and implementation of Frank, a strict functional programming language with a bidirectional effect type system designed from the ground up around a novel variant of Plotkin and Pretnar's effect handler abstraction. Effect handlers provide an abstraction for modular effectful programming: a handler acts as an interpreter for a collection of commands whose interfaces are statically tracked by the type system. However, Frank eliminates the need for an additional effect handling construct by generalising the basic mechanism of functional abstraction itself. A function is simply the special case of a Frank operator that interprets no commands. Moreover, Frank's operators can be multihandlers which simultaneously interpret commands from several sources at once, without disturbing the direct style of functional programming with values. Effect typing in Frank employs a novel form of effect polymorphism which avoid mentioning effect variables in source code. This is achieved by propagating an ambient ability inwards, rather than accumulating unions of potential effects outwards. We introduce Frank by example, and then give a formal account of the Frank type system and its semantics. We introduce Core Frank by elaborating Frank operators into functions, case expressions, and unary handlers, and then give a sound small-step operational semantics for Core Frank. Programming with effects and handlers is in its infancy. We contribute an exploration of future possibilities, particularly in combination with other forms of rich type system.

We explore the design and implementation of Frank, a strict functional programming language with a bidirectional effect type system designed from the ground up around a novel variant of Plotkin and Pretnar's effect handler abstraction. Effect handlers provide an abstraction for modular effectful programming: a handler acts as an interpreter for a collection of commands whose interfaces are statically tracked by the type system. However, Frank eliminates the need for an additional effect handling construct by generalising the basic mechanism of functional abstraction itself. A function is simply the special case of a Frank operator that interprets no commands. Moreover, Frank's operators can be multihandlers which simultaneously interpret commands from several sources at once, without disturbing the direct style of functional programming with values. Effect typing in Frank employs a novel form of effect polymorphism which avoid mentioning effect variables in source code. This is achieved by propagating an ambient ability inwards, rather than accumulating unions of potential effects outwards. We introduce Frank by example, and then give a formal account of the Frank type system and its semantics. We introduce Core Frank by elaborating Frank operators into functions, case expressions, and unary handlers, and then give a sound small-step operational semantics for Core Frank. Programming with effects and handlers is in its infancy. We contribute an exploration of future possibilities, particularly in combination with other forms of rich type system.

In these lecture notes we explain how multi-user web applications can be developed in a programming style that favors tasks as main building block for the construction of such systems. A task is work that has to be performed by human-beings and computers working together on the internet. This concept has been implemented in the iTask framework as a monadic combinator library that is embedded in the pure and lazy functional programming language Clean. These lecture notes consist of many examples and exercises, and also discusses the foundation of both the iTask system and task-oriented programming.

The notation of functional programming (FP) provides a clear and general syntax for writing programs which have extremely simple semantics and exhibit a clear hierarchical structure. Unfortunately, functional languages have a reputation of being hard to learn. This paper suggests an FP style of programming in which programmers deal with graphs as primary representations in programming, editing and executing programs. Programming becomes constructing system by which programs are built up as structured assemblies of functions. The programming technique developed in this paper follows four steps: (1) to define object types; (2) to define type clauses; (3) to construct program graphs; and (4) to automatically convert program graphs into FP programs. These programming processes help programmers easily form clear and correct mental images of a program's structure and function.

We present a breadth-first, lecture-and lab-based approach to introducing Computer Science that uses functional programming.Functional programming provides a lowoverhead introduction to programming (no types, few constructs, and little syntax), enabling students to write, in their first semester, programs sophisticated enough to exemplify important concepts of Computer Science.It also encourages good programming style (modular design and testing, e.g.) and serves as an introduction to an important problem-solving paradigm.The course gives the students a broad overview of Computer Science and helps them gauge their interest in the field.

We present a breadth-first, lecture- and lab-based approach to introducing Computer Science that uses functional programming. Functional programming provides a low-overhead introduction to programming (no types, few constructs, and little syntax), enabling students to write, in their first semester, programs sophisticated enough to exemplify important concepts of Computer Science. It also encourages good programming style (modular design and testing, e.g.) and serves as an introduction to an important problem-solving paradigm. The course gives the students a broad overview of Computer Science and helps them gauge their interest in the field.