Elaborator reflection : extending Idris in Idris

Many programming languages and proof assistants are defined by elaboration from a high-level language with a great deal of implicit information to a highly explicit core language. In many advanced languages, these elaboration facilities contain powerful tools for program construction, but these tools are rarely designed to be repurposed by users. We describe elaborator reflection, a paradigm for metaprogramming in which the elaboration machinery is made directly available to metaprograms, as well as a concrete realization of elaborator reflection in Idris, a functional language with full dependent types. We demonstrate the applicability of Idris’s reflected elaboration framework to a number of realistic problems, we discuss the motivation for the specific features of its design, and we explore the broader meaning of elaborator reflection as it can relate to other languages.Postprin

Against a Universal Definition of 'Type'

What is the definition of 'type'? Having a clear and precise answer to this question would avoid many misunderstandings and prevent meaningless discussions that arise from them. But having such clear and precise answer to this question would also hurt science, "hamper the growth of knowledge" and "deflect the course of investigation into narrow channels of things already understood". In this essay, I argue that not everything we work with needs to be precisely defined. There are many definitions used by different communities, but none of them applies universally. A brief excursion into philosophy of science shows that this is not just tolerable, but necessary for progress. Philosophy also suggests how we can think about this imprecise notion of type

Types from Data: Making Structured Data First-class Citizens in F#

Most modern applications interact with external services and access data in structured formats such as XML, JSON and CSV. Static type systems do not understand such formats, often making data access more cumbersome. Should we give up and leave the messy world of external data to dynamic typing and runtime checks? Of course, not! We present F# Data, a library that integrates external structured data into F#. As most real-world data does not come with an explicit schema, we develop a shape inference algorithm that infers a shape from representative sample documents. We then integrate the inferred shape into the F# type system using type providers. We formalize the process and prove a relative type soundness theorem. Our library significantly reduces the amount of data access code and it provides additional safety guarantees when contrasted with the widely used weakly typed techniques

Seamless, correct, and generic programming over serialised data

In typed functional languages, one can typically only manipulate data in a type-safe manner if it first has been deserialised into an in-memory tree represented as a graph of nodes-as-structs and subterms-as-pointers. We demonstrate how we can use QTT as implemented in \idris{} to define a small universe of serialised datatypes, and provide generic programs allowing users to process values stored contiguously in buffers. Our approach allows implementors to prove the full functional correctness by construction of the IO functions processing the data stored in the buffer

Journées Francophones des Langages Applicatifs 2018

National audienceLes 29èmes journées francophones des langages applicatifs (JFLA) se déroulent en 2018 à l'observatoire océanographique de Banyuls-sur-Mer. Les JFLA réunissent chaque année, dans un cadre convivial, concepteurs, développeurs et utilisateurs des langages fonctionnels, des assistants de preuve et des outils de vérification de programmes en présentant des travaux variés, allant des aspects les plus théoriques aux applications industrielles.Cette année, nous avons sélectionné 9 articles de recherche et 8 articles courts. Les thématiques sont variées : preuve formelle, vérification de programmes, modèle mémoire, langages de programmation, mais aussi théorie de l'homotopieet blockchain

Unification of Compile-Time and Runtime Metaprogramming in Scala

Metaprogramming is a technique that consists in writing programs that treat other programs as data. This paradigm of software development contributes to a multitude of approaches that improve programmer productivity, including code generation, program analysis and domain-specific languages. Many programming languages and runtime systems provide support for metaprogramming. Programming platforms often distinguish the notions of compile-time and runtime metaprogramming, depending on the phase of the program lifecycle when metaprograms execute. It is common for different lifecycle phases to be hosted in different environ- ments, so it is also common for different kinds of metaprogramming to provide different capabilities to metaprogrammers. In this dissertation, we present an exploration of the idea of unifying compile-time and runtime metaprogramming in Scala. We focus on the practical aspect of the exploration; most of the described designs are available as popular software products, and some of them have become part of the standard distribution of Scala. First, guided by the motivation to consolidate disparate metaprogramming techniques available in earlier versions of Scala, we introduce scala.reflect, a unified metaprogram- ming framework that uses a language model derived from the Scala compiler to run metaprograms both at compile time and at runtime. Secondly, armed by the newfound metaprogramming powers, we describe Scala macros, a language-integrated compile-time metaprogramming facility based on scala.reflect. Thanks to the comprehensive nature of scala.reflect, macros are able to work with both syntactic and semantic information about Scala programs, enabling a wide range of previously impractical or impossible use cases. Finally, based on our experience and user feedback, we identify key strengths and weaknesses of scala.reflect and macros. We propose scala.meta, a new unified metapro- gramming framework, and inline/meta, a new macro system based on scala.meta, that take the best from their predecessors and address the most important problems

FSCL: Homogeneous programming, scheduling and execution on heterogeneous platforms

The last few years has seen activity towards programming models, languages and frameworks to address the increasingly wide range and broad availability of heterogeneous computing resources through raised programming abstraction and portability across different platforms. The effort spent in simplifying parallel programming across heterogeneous platforms is often outweighed by the need for low-level control over computation setup and execution and by performance opportunities that are missed due to the overhead introduced by the additional abstraction. Moreover, despite the ability to port parallel code across devices, each device is generally characterised by a restricted set of computations that it can execute outperforming the other devices in the system. The problem is therefore to schedule computations on increasingly popular multi-device heterogeneous platforms, helping to choose the best device among the available ones each time a computation has to execute. Our Ph.D. research investigates the possibilities to address the problem of programming and execution abstraction on heterogeneous platforms while helping to dynamically and transparently exploit the computing power of such platforms in a device-aware fashion