Extensible pattern matching via a lightweight language extension

Pattern matching of algebraic data types (ADTs) is a standard feature in typed functional programming languages, but it is well known that it interacts poorly with abstraction. While several partial solutions to this problem have been proposed, few have been implemented or used. This paper describes an extension to the .NET language F# called active patterns , which supports pattern matching over abstract representations of generic heterogeneous data such as XML and term structures, including where these are represented via object models in other .NET languages. Our design is the first to incorporate both ad hoc pattern matching functions for partial decompositions and "views" for total decompositions, and yet remains a simple and lightweight extension. We give a description of the language extension along with numerous motivating examples. Finally we describe how this feature would interact with other reasonable and related language extensions: existential types quantified at data discrimination tags, GADTs, and monadic generalizations of pattern matching.

Pattern matching is a powerful programming concept which has proven its merits in declarative programming. The absence of pattern-matching in object-oriented programming languages is felt especially when tackling source code processing problems. But existing proposals for pattern matching in such languages rely on language extension, which makes their adoption overly intrusive. We propose an approach to support pattern matching in mainstream object-oriented languages without language extension. In this approach, a pattern is a first-class entity, which can be created, be passed as argument, and receive method invocations, just like any other object. We demonstrate how our approach can be used in conjunction with existing parser generators to perform pattern matching on various kinds of abstract syntax representation. We elaborate our approach to include concrete syntax patterns, and mixing of patterns and visitors for the construction of sophisticated syntax tree traversals.

We propose an extension of the join-calculus with pattern matching on algebraic data types. Our initial motivation is twofold: to provide an intuitive semantics of the interaction between concurrency and pattern matching; to define a practical compilation scheme from extended join-definitions into ordinary ones plus ML pattern matching. To assess the correctness of our compilation scheme, we develop a theory of the applied join-calculus, a calculus with value-passing and value matching.KeywordsPattern MatchTopological OrderMessage ContentClosed ProcessReaction RuleThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Developing programming languages is a difficult task that requires a lot of time, effort, and expertise. Reusable programming language components make this task easier, by allowing language designers to grab off-the-shelf components for common language features. Modern functional programming languages, however, lack support for reuse of definitions, and thus language components defined using algebraic data types and pattern matching functions cannot be reused without modifying or copying existing code. To improve the situation, we introduce CS, a functional meta-language for developing reusable programming language components, that features built-in support for extensible data types and functions, as well as effects and handlers. In CS, we can define language components using algebraic data types and pattern matching functions, such that we can compose language components into larger languages and define new interpretations for existing components without modifying existing definitions.

Scala is a new programming language developed at EPFL and incorporating the most important concepts of object-oriented and functional languages. It aims at integrating well with the Java and .NET platforms: their respective libraries are accessible without glue code, and the compiler can produce programs for both virtual machines. This thesis focuses on the compilation of two important concepts of Scala : mixin inheritance and run time types. The compilation techniques are presented in the context of the Java virtual machine, but could be adapted easily to other similar environments. Mixin inheritance is a relatively recent form of inheritance, offering new capabilities compared to single inheritance, without the complexity of multiple inheritance. We propose two implementation techniques for mixin inheritance: code copying and delegation. The implementation used in the Scala compiler is then presented and justified. Run time types make it possible for a program to examine the type of its values during execution. This possibility is interesting in itself, offering new capabilities to the programmer. Furthermore, run time types are also required to implement other high level concepts, like pattern matching, type-safe serialisation and reflection. We propose an implementation technique based on the representation of types as values, and show how to use the run time types of the underlying virtual machine to implement those of Scala. The techniques presented in this thesis have been implemented in our Scala compiler, scalac. This enabled us to evaluate these techniques, in particular their impact on the performances of programs. This evaluation was performed on several real, non-trivial programs.

Dependent pattern matching is an intuitive way to write programs and proofs in dependently typed languages. It is reminiscent of both pattern matching in functional languages and case analysis in on-paper mathematics. However, in general it is incompatible with new type theories such as homotopy type theory (HoTT). As a consequence, proofs in such theories are typically harder to write and to understand. The source of this incompatibility is the reliance of dependent pattern matching on the so-called K axiom - also known as the uniqueness of identity proofs - which is inadmissible in HoTT. The Agda language supports an experimental criterion to detect definitions by pattern matching that make use of the K axiom, but so far it lacked a formal correctness proof.In this paper, we propose a new criterion for dependent pattern matching without K, and prove it correct by a translation to eliminators in the style of Goguen et al. (2006). Our criterion both allows more good definitions than existing proposals, and solves a previously undetected problem in the criterion offered by Agda. It has been implemented in Agda and is the first to be supported by a formal proof. Thus it brings the benefits of dependent pattern matching to contexts where we cannot assume K, such as HoTT. It also points the way to new forms of dependent pattern matching, for example on higher inductive types.

Compilation is all about tree rewriting. In functional languages where all data is tree-shaped, tree rewriting is facilitated by pattern matching, but data immutability leads to copying for each update. In object-oriented languages like Java or C++, a standard approach is to use the visitor pattern, which increases modularization but also adds indirection and introduces boilerplate code. In this paper, we introduce Trieste -- a novel tree-rewriting DSL, combining the power of C++ with the expressivity of pattern matching. In Trieste, sequences of rewrite passes can be used to read a file to produce an abstract syntax tree (AST), convert from one AST to another, or write an AST to disk. Each pass rewrites an AST in place using subtree pattern matching, where the result is dynamically checked for well-formedness. Checking the well-formedness of trees dynamically enables flexibly changing the tree structure without having to define new data types for each intermediate representation. The well-formedness specification can also be used for scoped name binding and generating random well-formed trees for fuzz testing in addition to checking the shape of trees. Trieste has been used to build fully compliant parsers for YAML and JSON, a transpiler from YAML to JSON, and a compiler and interpreter for the policy language Rego.

Pattern matching is a key concept for rule-based expert systems. Simple pattern interpreters appear in nearly every book on Lisp. Pattern matching is also a useful tool for case analyses as provided by functional languages such as ML or Miranda™. These two uses are somewhat different since functional languages emphasize a discrimination based on types while Lisp, or Plasma, make use of S-expressions or segments of S-expressions within patterns. The paper presents an intermediate language for patterns and its denotational semantics. This reduced language is powerful enough to express boolean composition of patterns as well as segment handling and unbounded pattern repetition. A compiler is then defined which translates patterns into functional code. We discuss some compilation variant as well as the integration of the pattern sub-language into Lisp. These capabilities make pattern matching an useful and efficient tool for a wide class of applicative languages and allow to incorporate into patterns more knowledge about the form or gestalt of the data to be matched.

Object-oriented programming languages are suitable for describing real-world objects, functional programming languages for algebraic values. In this paper we propose an object-oriented functional programming language, called TOFL, which combines many desired properties of the two paradigms. In particular, TOFL unifies object classes, inheritance, (method) redefinitions and late binding as in object-oriented languages, algebraic data types, higher-order functions, type classes and type inference (without type reconstruction in this paper) as in functional languages. We translate TOFL into a stratified and explicitly typed λ-calculus T with overloaded functions, where redefinitions and late binding become late binding of overloaded functions. The operational semantics of T gives a semantics and a simple prototyping implementation of TOFL.

Objectives: The main objective of this paper is to identify suitable programming concepts from Functional Programming paradigm concerning low resource devices development and eventually contribute an approach for design level optimization. Methods: Experiments have been conducted, CPU time and memory consumptions (Private Bytes) were measured. Findings: The research results indicated that Pattern Matching, Lazy, Curried, Tail Recursion, Functional Composition, Referential Transparency and Higher Order Functions with functions as parameters concepts consumed less CPU and memory resources compared to their alternative concepts. This paper suggests that the above mentioned concepts can be applied by any software engineering practitioners in designing resource efficient constructs for software applications. Applications: Using these guidelines substantial performance growth can be formed and at the same time, performance degradation issues can be easily avoided. Eventually, this paper contributes a way to optimize the Functional Programming design at design level.

A robust software component fulfills a contract: it expects data satisfying a certain property and promises to return data satisfying another property. The object-oriented community uses the design-by-contract approach extensively. Proposals for language extensions that add contracts to higher-order functional programming have appeared recently. In this paper we propose an embedded domain-specific language for typed, higher-order and first-class contracts, which is both more expressive than previous proposals, and allows for a more informative blame assignment. We take some first steps towards an algebra of contracts, and we show how to define a generic contract combinator for arbitrary algebraic data types. The contract language is implemented as a library in Haskell using the concept of generalised algebraic data types.

Algebraic data types are the natural target of pattern-matching functions. When the type is parametric then the pattern-matching functions typically support parametric polymorphism. In addition, bondi supports generic functional programming by introducing a small family of primitive, or representing data types, which can be used to define generic functions such as map, with one case for each primitive constructor. Each resulting case has a different type, so type specialisation is involved, too. During a type declaration, additional cases can be added to existing functions.

In many applications, such as algebraic data type specifications and equational programming, equations are intended to define a certain standard model, called the "initial model." Reasoning about algebraic data types and equational programs thus requires proof methods for this initial algebra semantics. Such proof methods typically employ some induction scheme, e. g., induction on the structure of terms. We shall discuss an alternative approach—proof by consistency—that can be applied to equational theories that are presented as ground convergent rewrite systems.

Datalog is a carefully restricted logic programming language. What makes Datalog attractive is its declarative fixpoint semantics: Datalog queries consist of simple Horn clauses, yet Datalog solvers efficiently compute all derivable tuples even for recursive queries. However, as we argue in this paper, Datalog is ill-suited as a programming language and Datalog programs are hard to write and maintain. We propose a “new” frontend for Datalog: functional programming with sets called functional IncA. While programmers write recursive functions over algebraic data types and sets, we transparently translate all code to Datalog relations. However, we retain Datalog’s strengths: Functions that generate sets can encode arbitrary relations and mutually recursive functions have fixpoint semantics. We also ensure that the generated Datalog program terminates whenever the original functional program terminates, so that we can apply off-the-shelve bottom-up Datalog solvers. We demonstrate the versatility and ease of use of functional IncA by implementing a type checker, a program transformation, an interpreter of the untyped lambda calculus, two data-flow analyses, and clone detection of Java bytecode.

In Chapters 3,4, and 6 we covered three well-known programming paradigms in F#: functional, imperative, and objectoriented programming. In this chapter, we cover techniques and constructs related to what is essentially a fourth programming paradigm, which we call languageoriented programming. The word language can have a number of meanings in this context. For example, take the simple language of arithmetic expressions and algebra that you learned in high-school mathematics, made up of named variables such as x and y and composite expressions such as x+y, xy,−x, and x 2 . For the purposes of this chapter, this language can have a number of manifestations: One or more concrete representations, for example, using an ASCII text format or an XML representation of arithmetic expressions. One or more abstract representations, for example, as F# values representing the normalized form of an arithmetic expression tree. One or more computational representations, either by functions that compute the values of arithmetic expressions or via other engines that perform analysis, interpretation, compilation, execution, or transformation on language fragments. These can be implemented in F#, in another .NET language, or in external engines.