Correctness of an STM Haskell implementation

A concurrent implementation of software transactional memory in Concurrent Haskell using a call-by-need functional language with processes and futures is given. The description of the small-step operational semantics is precise and explicit, and employs an early abort of conflicting transactions. A proof of correctness of the implementation is given for a contextual semantics with may- and should-convergence. This implies that our implementation is a correct evaluator for an abstract specification equipped with a big-step semantics

Programming Language Techniques for Natural Language Applications

It is easy to imagine machines that can communicate in natural language. Constructing such machines is more difficult. The aim of this thesis is to demonstrate how declarative grammar formalisms that distinguish between abstract and concrete syntax make it easier to develop natural language applications. We describe how the type-theorectical grammar formalism Grammatical Framework (GF) can be used as a high-level language for natural language applications. By taking advantage of techniques from the field of programming language implementation, we can use GF grammars to perform portable and efficient parsing and linearization, generate speech recognition language models, implement multimodal fusion and fission, generate support code for abstract syntax transformations, generate dialogue managers, and implement speech translators and web-based syntax-aware editors. By generating application components from a declarative grammar, we can reduce duplicated work, ensure consistency, make it easier to build multilingual systems, improve linguistic quality, enable re-use across system domains, and make systems more portable

Static Application-Level Race Detection in STM Haskell using Contracts

Writing concurrent programs is a hard task, even when using high-level synchronization primitives such as transactional memories together with a functional language with well-controlled side-effects such as Haskell, because the interferences generated by the processes to each other can occur at different levels and in a very subtle way. The problem occurs when a thread leaves or exposes the shared data in an inconsistent state with respect to the application logic or the real meaning of the data. In this paper, we propose to associate contracts to transactions and we define a program transformation that makes it possible to extend static contract checking in the context of STM Haskell. As a result, we are able to check statically that each transaction of a STM Haskell program handles the shared data in a such way that a given consistency property, expressed in the form of a user-defined boolean function, is preserved. This ensures that bad interference will not occur during the execution of the concurrent program.Comment: In Proceedings PLACES 2013, arXiv:1312.2218. [email protected]; [email protected]

How functional programming mattered

In 1989 when functional programming was still considered a niche topic, Hughes wrote a visionary paper arguing convincingly ‘why functional programming matters’. More than two decades have passed. Has functional programming really mattered? Our answer is a resounding ‘Yes!’. Functional programming is now at the forefront of a new generation of programming technologies, and enjoying increasing popularity and influence. In this paper, we review the impact of functional programming, focusing on how it has changed the way we may construct programs, the way we may verify programs, and fundamentally the way we may think about programs

Palgol: A High-Level DSL for Vertex-Centric Graph Processing with Remote Data Access

Pregel is a popular distributed computing model for dealing with large-scale graphs. However, it can be tricky to implement graph algorithms correctly and efficiently in Pregel's vertex-centric model, especially when the algorithm has multiple computation stages, complicated data dependencies, or even communication over dynamic internal data structures. Some domain-specific languages (DSLs) have been proposed to provide more intuitive ways to implement graph algorithms, but due to the lack of support for remote access --- reading or writing attributes of other vertices through references --- they cannot handle the above mentioned dynamic communication, causing a class of Pregel algorithms with fast convergence impossible to implement. To address this problem, we design and implement Palgol, a more declarative and powerful DSL which supports remote access. In particular, programmers can use a more declarative syntax called chain access to naturally specify dynamic communication as if directly reading data on arbitrary remote vertices. By analyzing the logic patterns of chain access, we provide a novel algorithm for compiling Palgol programs to efficient Pregel code. We demonstrate the power of Palgol by using it to implement several practical Pregel algorithms, and the evaluation result shows that the efficiency of Palgol is comparable with that of hand-written code.Comment: 12 pages, 10 figures, extended version of APLAS 2017 pape

Supermonads: one notion to bind them all

Several popular generalizations of monads have been implemented in Haskell. Unfortunately, because the shape of the associated type constructors do not match the standard Haskell monad interface, each such implementation provides its own type class and versions of associated library functions. Furthermore, simultaneous use of different monadic notions can be cumbersome as it in general is necessary to be explicit about which notion is used where. In this paper we introduce supermonads: an encoding of monadic notions that captures several different generalizations along with a version of the standard library of monadic functions that work uniformly with all of them. As standard Haskell type inference does not work for supermonads due to their generality, our supermonad implementation is accompanied with a language extension, in the form of a plugin for the Glasgow Haskell Compiler (GHC), that allows type inference for supermonads, obviating the need for manual annotations

Constraint Generation for the Jeeves Privacy Language

Our goal is to present a completed, semantic formalization of the Jeeves privacy language evaluation engine, based on the original Jeeves constraint semantics defined by Yang et al at POPL12, but sufficiently strong to support a first complete implementation thereof. Specifically, we present and implement a syntactically and semantically completed concrete syntax for Jeeves that meets the example criteria given in the paper. We also present and implement the associated translation to J, but here formulated by a completed and decompositional operational semantic formulation. Finally, we present an enhanced and decompositional, non-substitutional operational semantic formulation and implementation of the J evaluation engine (the dynamic semantics) with privacy constraints. In particular, we show how implementing the constraints can be defined as a monad, and evaluation can be defined as monadic operation on the constraint environment. The implementations are all completed in Haskell, utilizing its almost one-to-one capability to transparently reflect the underlying semantic reasoning when formalized this way. In practice, we have applied the "literate" program facility of Haskell to this report, a feature that enables the source LATEX to also serve as the source code for the implementation (skipping the report-parts as comment regions). The implementation is published as a github project

Semantic methods for functional hybrid modelling

Equation-based modelling languages have become a vital tool in many areas of science and engineering. Functional Hybrid Modelling (FHM) is an approach to equation-based modelling that allows the behaviour of a physical system to be expressed as a modular hierarchy of undirected equations. FHM supports a variety of advanced language features — such as higher-order models and variable system structure — that sets it apart from the majority of other modelling languages. However, the inception of these new features has not been accompanied by the semantic tools required to effectively use and understand them. Specifically, there is a lack of static safety assurances for dynamic models and the semantics of the aforementioned language features are poorly understood. Static safety guarantees are highly desirable as they allow problems that may cause an equation system to become unsolvable to be detected early, during compilation. As a result, the use of static analysis techniques to enforce structural invariants (e.g. that there are the same number of equations as unknowns) is now in use in main-stream equation-based languages like Modelica. Unfortunately, the techniques employed by these languages are somewhat limited, both in their capacity to deal with advanced language features and also by the spectrum of invariants they are able to enforce. Formalising the semantics of equation-based languages is also important. Semantics allow us to better understand what a program is doing during execution, and to prove that this behaviour meets with our expectation. They also allow different implementations of a language to agree with one another, and can be used to demonstrate the correctness of a compiler or interpreter. However, current attempts to formalise such semantics typically fall short of describing advanced features, are not compositional, and/or fail to show correctness. This thesis provides two major contributions to equation-based languages. Firstly, we develop a refined type system for FHM capable of capturing a larger number of structural anomalies than is currently possible with existing methods. Secondly, we construct a compositional semantics for the discrete aspects of FHM, and prove a number of key correctness properties