Heterogeneous substitution systems revisited

Matthes and Uustalu (TCS 327(1-2):155-174, 2004) presented a categorical description of substitution systems capable of capturing syntax involving binding which is independent of whether the syntax is made up from least or greatest fixed points. We extend this work in two directions: we continue the analysis by creating more categorical structure, in particular by organizing substitution systems into a category and studying its properties, and we develop the proofs of the results of the cited paper and our new ones in UniMath, a recent library of univalent mathematics formalized in the Coq theorem prover.Comment: 24 page

Fibrational induction rules for initial algebras

This paper provides an induction rule that can be used to prove properties of data structures whose types are inductive, i.e., are carriers of initial algebras of functors. Our results are semantic in nature and are inspired by Hermida and Jacobs’ elegant algebraic formulation of induction for polynomial data types. Our contribution is to derive, under slightly different assumptions, an induction rule that is generic over all inductive types, polynomial or not. Our induction rule is generic over the kinds of properties to be proved as well: like Hermida and Jacobs, we work in a general fibrational setting and so can accommodate very general notions of properties on inductive types rather than just those of particular syntactic forms. We establish the correctness of our generic induction rule by reducing induction to iteration. We show how our rule can be instantiated to give induction rules for the data types of rose trees, finite hereditary sets, and hyperfunctions. The former lies outside the scope of Hermida and Jacobs’ work because it is not polynomial; as far as we are aware, no induction rules have been known to exist for the latter two in a general fibrational framework. Our instantiation for hyperfunctions underscores the value of working in the general fibrational setting since this data type cannot be interpreted as a set

Fibrational Induction Rules for Initial Algebras

This paper provides an induction rule that can be used to prove properties of data structures whose types are inductive, i.e., are carriers of initial algebras of functors. Our results are semantic in nature and are inspired by Hermida and Jacobs’ elegant algebraic formulation of induction for polynomial data types. Our contribution is to derive, under slightly different assumptions, an induction rule that is generic over all inductive types, polynomial or not. Our induction rule is generic over the kinds of properties to be proved as well: like Hermida and Jacobs, we work in a general fibrational setting and so can accommodate very general notions of properties on inductive types rather than just those of particular syntactic forms. We establish the correctness of our generic induction rule by reducing induction to iteration. We show how our rule can be instantiated to give induction rules for the data types of rose trees, definite hereditary sets, and hyperfunctions. The former lies outside the scope of Hermida and Jacobs’ work because it is not polynomial; as far as we are aware, no induction rules have been known to exist for the latter two in a general fibrational framework. Our instantiation for hyperfunctions underscores the value of working in the general fibrational setting since this data type cannot be interpreted as a set

Generic Fibrational Induction

This paper provides an induction rule that can be used to prove properties of data structures whose types are inductive, i.e., are carriers of initial algebras of functors. Our results are semantic in nature and are inspired by Hermida and Jacobs' elegant algebraic formulation of induction for polynomial data types. Our contribution is to derive, under slightly different assumptions, a sound induction rule that is generic over all inductive types, polynomial or not. Our induction rule is generic over the kinds of properties to be proved as well: like Hermida and Jacobs, we work in a general fibrational setting and so can accommodate very general notions of properties on inductive types rather than just those of a particular syntactic form. We establish the soundness of our generic induction rule by reducing induction to iteration. We then show how our generic induction rule can be instantiated to give induction rules for the data types of rose trees, finite hereditary sets, and hyperfunctions. The first of these lies outside the scope of Hermida and Jacobs' work because it is not polynomial, and as far as we are aware, no induction rules have been known to exist for the second and third in a general fibrational framework. Our instantiation for hyperfunctions underscores the value of working in the general fibrational setting since this data type cannot be interpreted as a set.Comment: For Special Issue from CSL 201

Foundational nonuniform (co)datatypes for higher-order logic

Nonuniform (or “nested” or “heterogeneous”) datatypes are recursively defined types in which the type arguments vary recursively. They arise in the implementation of finger trees and other efficient functional data structures. We show how to reduce a large class of nonuniform datatypes and codatatypes to uniform types in higher-order logic. We programmed this reduction in the Isabelle/HOL proof assistant, thereby enriching its specification language. Moreover, we derive (co)recusion and (co)induction principles based on a weak variant of parametricity

Foundational nonuniform (co)datatypes for higher-order logic

Nonuniform (or “nested” or “heterogeneous”) datatypes are recursively defined types in which the type arguments vary recursively. They arise in the implementation of finger trees and other efficient functional data structures. We show how to reduce a large class of nonuniform datatypes and codatatypes to uniform types in higher-order logic. We programmed this reduction in the Isabelle/HOL proof assistant, thereby enriching its specification language. Moreover, we derive (co)recusion and (co)induction principles based on a weak variant of parametricity

Generic Fibrational Induction

This paper provides an induction rule that can be used to prove properties of data structures whose types are inductive, i.e., are carriers of initial algebras of functors. Our results are semantic in nature and are inspired by Hermida and Jacobs’ elegant algebraic formulation of induction for polynomial data types. Our contribution is to derive, under slightly different assumptions, a sound induction rule that is generic over all inductive types, polynomial or not. Our induction rule is generic over the kinds of properties to be proved as well: like Hermida and Jacobs, we work in a general fibrational setting and so can accommodate very general notions of properties on inductive types rather than just those of a particular syntactic form. We establish the soundness of our generic induction rule by reducing induction to iteration. We then show how our generic induction rule can be instantiated to give induction rules for the data types of rose trees, definite hereditary sets, and hyperfunctions. The first of these lies outside the scope of Hermida and Jacobs’ work because it is not polynomial, and as far as we are aware, no induction rules have been known to exist for the second and third in a general fibrational framework. Our instantiation for hyperfunctions underscores the value of working in the general fibrational setting since this data type cannot be interpreted as a set

Parametricity for Nested Types and GADTs

This paper considers parametricity and its consequent free theorems for nested data types. Rather than representing nested types via their Church encodings in a higher-kinded or dependently typed extension of System F, we adopt a functional programming perspective and design a Hindley-Milner-style calculus with primitives for constructing nested types directly as fixpoints. Our calculus can express all nested types appearing in the literature, including truly nested types. At the level of terms, it supports primitive pattern matching, map functions, and fold combinators for nested types. Our main contribution is the construction of a parametric model for our calculus. This is both delicate and challenging. In particular, to ensure the existence of semantic fixpoints interpreting nested types, and thus to establish a suitable Identity Extension Lemma for our calculus, our type system must explicitly track functoriality of types, and cocontinuity conditions on the functors interpreting them must be appropriately threaded throughout the model construction. We also prove that our model satisfies an appropriate Abstraction Theorem, as well as that it verifies all standard consequences of parametricity in the presence of primitive nested types. We give several concrete examples illustrating how our model can be used to derive useful free theorems, including a short cut fusion transformation, for programs over nested types. Finally, we consider generalizing our results to GADTs, and argue that no extension of our parametric model for nested types can give a functorial interpretation of GADTs in terms of left Kan extensions and still be parametric

Parametricity For Primitive Nested Types

This paper considers parametricity and its resulting free theorems for nested data types. Rather than representing nested types via their Church encodings in a higher-kinded or dependently typed extension of System F, we adopt a functional programming perspective and design a Hindley-Milner-style calculus with primitives for constructing nested types directly as fixpoints. Our calculus can express all nested types appearing in the literature, including truly nested types. At the term level, it supports primitive pattern matching, map functions, and fold combinators for nested types. Our main contribution is the construction of a parametric model for our calculus. This is both delicate and challenging: to ensure the existence of semantic fixpoints interpreting nested types, and thus to establish a suitable Identity Extension Lemma for our calculus, our type system must explicitly track functoriality of types, and co-continuity conditions on the functors interpreting them must be appropriately threaded throughout the model construction. We prove that our model satisfies an appropriate Abstraction Theorem and verifies all standard consequences of parametricity for primitive nested types

Optimizing and Incrementalizing Higher-order Collection Queries by AST Transformation

In modernen, universellen Programmiersprachen sind Abfragen auf Speicher-basierten Kollektionen oft rechenintensiver als erforderlich. Während Datenbankenabfragen vergleichsweise einfach optimiert werden können, fällt dies bei Speicher-basierten Kollektionen oft schwer, denn universelle Programmiersprachen sind in aller Regel ausdrucksstärker als Datenbanken. Insbesondere unterstützen diese Sprachen meistens verschachtelte, rekursive Datentypen und Funktionen höherer Ordnung. Kollektionsabfragen können per Hand optimiert und inkrementalisiert werden, jedoch verringert dies häufig die Modularität und ist oft zu fehleranfällig, um realisierbar zu sein oder um Instandhaltung von entstandene Programm zu gewährleisten. Die vorliegende Doktorarbeit demonstriert, wie Abfragen auf Kollektionen systematisch und automatisch optimiert und inkrementalisiert werden können, um Programmierer von dieser Last zu befreien. Die so erzeugten Programme werden in derselben Kernsprache ausgedrückt, um weitere Standardoptimierungen zu ermöglichen. Teil I entwickelt eine Variante der Scala API für Kollektionen, die Staging verwendet um Abfragen als abstrakte Syntaxbäume zu reifizieren. Auf Basis dieser Schnittstelle werden anschließend domänenspezifische Optimierungen von Programmiersprachen und Datenbanken angewandt; unter anderem werden Abfragen umgeschrieben, um vom Programmierer ausgewählte Indizes zu benutzen. Dank dieser Indizes kann eine erhebliche Beschleunigung der Ausführungsgeschwindigkeit gezeigt werden; eine experimentelle Auswertung zeigt hierbei Beschleunigungen von durchschnittlich 12x bis zu einem Maximum von 12800x. Um Programme mit Funktionen höherer Ordnung durch Programmtransformation zu inkrementalisieren, wird in Teil II eine Erweiterung der Finite-Differenzen-Methode vorgestellt [Paige and Koenig, 1982; Blakeley et al., 1986; Gupta and Mumick, 1999] und ein erster Ansatz zur Inkrementalisierung durch Programmtransformation für Programme mit Funktionen höherer Ordnung entwickelt. Dabei werden Programme zu Ableitungen transformiert, d.h. zu Programmen die Eingangsdifferenzen in Ausgangdifferenzen umwandeln. Weiterhin werden in den Kapiteln 12–13 die Korrektheit des Inkrementalisierungsansatzes für einfach-getypten und ungetypten λ-Kalkül bewiesen und Erweiterungen zu System F besprochen. Ableitungen müssen oft Ergebnisse der ursprünglichen Programme wiederverwenden. Um eine solche Wiederverwendung zu ermöglichen, erweitert Kapitel 17 die Arbeit von Liu and Teitelbaum [1995] zu Programmen mit Funktionen höherer Ordnung und entwickeln eine Programmtransformation solcher Programme im Cache-Transfer-Stil. Für eine effiziente Inkrementalisierung ist es weiterhin notwendig, passende Grundoperationen auszuwählen und manuell zu inkrementalisieren. Diese Arbeit deckt einen Großteil der wichtigsten Grundoperationen auf Kollektionen ab. Die Durchführung von Fallstudien zeigt deutliche Laufzeitverbesserungen sowohl in Praxis als auch in der asymptotischen Komplexität.In modern programming languages, queries on in-memory collections are often more expensive than needed. While database queries can be readily optimized, it is often not trivial to use them to express collection queries which employ nested data and first-class functions, as enabled by functional programming languages. Collection queries can be optimized and incrementalized by hand, but this reduces modularity, and is often too error-prone to be feasible or to enable maintenance of resulting programs. To free programmers from such burdens, in this thesis we study how to optimize and incrementalize such collection queries. Resulting programs are expressed in the same core language, so that they can be subjected to other standard optimizations. To enable optimizing collection queries which occur inside programs, we develop a staged variant of the Scala collection API that reifies queries as ASTs. On top of this interface, we adapt domain-specific optimizations from the fields of programming languages and databases; among others, we rewrite queries to use indexes chosen by programmers. Thanks to the use of indexes we show significant speedups in our experimental evaluation, with an average of 12x and a maximum of 12800x. To incrementalize higher-order programs by program transformation, we extend finite differencing [Paige and Koenig, 1982; Blakeley et al., 1986; Gupta and Mumick, 1999] and develop the first approach to incrementalization by program transformation for higher-order programs. Base programs are transformed to derivatives, programs that transform input changes to output changes. We prove that our incrementalization approach is correct: We develop the theory underlying incrementalization for simply-typed and untyped λ-calculus, and discuss extensions to System F. Derivatives often need to reuse results produced by base programs: to enable such reuse, we extend work by Liu and Teitelbaum [1995] to higher-order programs, and develop and prove correct a program transformation, converting higher-order programs to cache-transfer-style. For efficient incrementalization, it is necessary to choose and incrementalize by hand appropriate primitive operations. We incrementalize a significant subset of collection operations and perform case studies, showing order-of-magnitude speedups both in practice and in asymptotic complexity