The HERMIT in the Tree

This paper describes our experience using the HERMIT tool- kit to apply well-known transformations to the internal core language of the Glasgow Haskell Compiler. HERMIT provides several mechanisms to support writing general-purpose transformations: a domain-specific language for strategic programming specialized to GHC's core language, a library of primitive rewrites, and a shell-style{based scripting language for interactive and batch usage. There are many program transformation techniques that have been described in the literature but have not been mechanized and made available inside GHC - either because they are too specialized to include in a general-purpose compiler, or because the developers' interest is in theory rather than implementation. The mechanization process can often reveal pragmatic obstacles that are glossed over in pen-and-paper proofs; understanding and removing these obstacles is our concern. Using HERMIT, we implement eleven examples of three program transformations, report on our experience, and describe improvements made in the process

HERMIT: Mechanized Reasoning during Compilation in the Glasgow Haskell Compiler

It is difficult to write programs which are both correct and fast. A promising approach, functional programming, is based on the idea of using pure, mathematical functions to construct programs. With effort, it is possible to establish a connection between a specification written in a functional language, which has been proven correct, and a fast implementation, via program transformation. When practiced in the functional programming community, this style of reasoning is still typically performed by hand, by either modifying the source code or using pen-and-paper. Unfortunately, performing such semi-formal reasoning by directly modifying the source code often obfuscates the program, and pen-and-paper reasoning becomes outdated as the program changes over time. Even so, this semi-formal reasoning prevails because formal reasoning is time-consuming, and requires considerable expertise. Formal reasoning tools often only work for a subset of the target language, or require programs to be implemented in a custom language for reasoning. This dissertation investigates a solution, called HERMIT, which mechanizes reasoning during compilation. HERMIT can be used to prove properties about programs written in the Haskell functional programming language, or transform them to improve their performance. Reasoning in HERMIT proceeds in a style familiar to practitioners of pen-and-paper reasoning, and mechanization allows these techniques to be applied to real-world programs with greater confidence. HERMIT can also re-check recorded reasoning steps on subsequent compilations, enforcing a connection with the program as the program is developed. HERMIT is the first system capable of directly reasoning about the full Haskell language. The design and implementation of HERMIT, motivated both by typical reasoning tasks and HERMIT's place in the Haskell ecosystem, is presented in detail. Three case studies investigate HERMIT's capability to reason in practice. These case studies demonstrate that semi-formal reasoning with HERMIT lowers the barrier to writing programs which are both correct and fast

The Life Changing HERMIT: A Case Study of the Worker/Wrapper Transformation

In software engineering, altering a program's original implementation disconnects it from the model that produced it. Reconnecting the model and new implementations must be done in a way that does not decrease confidence in the design's correctness and performance. This thesis demonstrates that it is possible, in practice, to connect the model of Conway's Game of Life with new implementations, using the worker/wrapper transformation theory. This connection allows development to continue without the sacrifice of re-implementation. HERMIT is a tool that allows programs implemented in Haskell to be transformed during the compilation process, and has features capable of performing worker/wrapper transformations. Specifically in these experiments, HERMIT is used to apply syntax transformations to replace Life's linked-list based implementation with one that uses other data structures in an effort to explore alternative implementations and improve overall performance. Previous work has successfully performed the worker/wrapper conversion on an individual function using HERMIT. This thesis presents the first time that a programmer-directed worker/wrapper transformation has been attempted on an entire program. From this experiment, substantial observations have been made. These observations have led to proposed improvements to the HERMIT system, as well as the formal approach to the worker/wrapper transformation process

Theorem Provers as Libraries -- An Approach to Formally Verifying Functional Programs

Property-directed verification of functional programs tends to take one of two paths. First, is the traditional testing approach, where properties are expressed in the original programming language and checked with a collection of test data. Alternatively, for those desiring a more rigorous approach, properties can be written and checked with a formal tool; typically, an external proof system. This dissertation details a hybrid approach that captures the best of both worlds: the formality of a proof system paired with the native integration of an embedded, domain specific language (EDSL) for testing. At the heart of this hybridization is the titular concept -- a theorem prover as a library. The verification capabilities of this prover, HaskHOL, are introduced to a Haskell development environment as a GHC compiler plugin. Operating at the compiler level provides for a comparatively simpler integration and allows verification to co-exist with the numerous other passes that stand between source code and program

Worker/Wrapper/Makes It/Faster. In

Abstract Much research in program optimization has focused on formal approaches to correctness: proving that the meaning of programs is preserved by the optimisation. Paradoxically, there has been comparatively little work on formal approaches to efficiency: proving that the performance of optimized programs is actually improved. This paper addresses this problem for a general-purpose optimization technique, the worker/wrapper transformation. In particular, we use the call-by-need variant of improvement theory to establish conditions under which the worker/wrapper transformation is formally guaranteed to preserve or improve the time performance of programs in lazy languages such as Haskell

Programs for Cheap!

Abstract-Write down the definition of a recursion operator on a piece of paper. Tell me its type, but be careful not to let me see the operator's definition. I will tell you an optimization theorem that the operator satisfies. As an added bonus, I will also give you a proof of correctness for the optimisation, along with a formal guarantee about its effect on performance. The purpose of this paper is to explain these tricks

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