9,396 research outputs found

    Functional Baby Talk: Analysis of Code Fragments from Novice Haskell Programmers

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    What kinds of mistakes are made by novice Haskell developers, as they learn about functional programming? Is it possible to analyze these errors in order to improve the pedagogy of Haskell? In 2016, we delivered a massive open online course which featured an interactive code evaluation environment. We captured and analyzed 161K interactions from learners. We report typical novice developer behavior; for instance, the mean time spent on an interactive tutorial is around eight minutes. Although our environment was restricted, we gain some understanding of Haskell novice errors. Parenthesis mismatches, lexical scoping errors and do block misunderstandings are common. Finally, we make recommendations about how such beginner code evaluation environments might be enhanced

    How functional programming mattered

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    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

    RELEASE: A High-level Paradigm for Reliable Large-scale Server Software

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    Erlang is a functional language with a much-emulated model for building reliable distributed systems. This paper outlines the RELEASE project, and describes the progress in the rst six months. The project aim is to scale the Erlang's radical concurrency-oriented programming paradigm to build reliable general-purpose software, such as server-based systems, on massively parallel machines. Currently Erlang has inherently scalable computation and reliability models, but in practice scalability is constrained by aspects of the language and virtual machine. We are working at three levels to address these challenges: evolving the Erlang virtual machine so that it can work effectively on large scale multicore systems; evolving the language to Scalable Distributed (SD) Erlang; developing a scalable Erlang infrastructure to integrate multiple, heterogeneous clusters. We are also developing state of the art tools that allow programmers to understand the behaviour of massively parallel SD Erlang programs. We will demonstrate the e ectiveness of the RELEASE approach using demonstrators and two large case studies on a Blue Gene

    A Formal, Resource Consumption-Preserving Translation of Actors to Haskell

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    We present a formal translation of an actor-based language with cooperative scheduling to the functional language Haskell. The translation is proven correct with respect to a formal semantics of the source language and a high-level operational semantics of the target, i.e. a subset of Haskell. The main correctness theorem is expressed in terms of a simulation relation between the operational semantics of actor programs and their translation. This allows us to then prove that the resource consumption is preserved over this translation, as we establish an equivalence of the cost of the original and Haskell-translated execution traces.Comment: Pre-proceedings paper presented at the 26th International Symposium on Logic-Based Program Synthesis and Transformation (LOPSTR 2016), Edinburgh, Scotland UK, 6-8 September 2016 (arXiv:1608.02534

    Towards sound refactoring in erlang

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    Erlang is an actor-based programming language used extensively for building concurrent, reactive systems that are highly available and suff er minimum downtime. Such systems are often mission critical, making system correctness vital. Refactoring is code restructuring that improves the code but does not change behaviour. While using automated refactoring tools is less error-prone than performing refactorings manually, automated refactoring tools still cannot guarantee that the refactoring is correct, i.e., program behaviour is preserved. This leads to lack of trust in automated refactoring tools. We rst survey solutions to this problem proposed in the literature. Erlang refactoring tools as commonly use approximation techniques which do not guarantee behaviour while some other works propose the use of formal methodologies. In this work we aim to develop a formal methodology for refactoring Erlang code. We study behavioural preorders, with a special focus on the testing preorder as it seems most suited to our purpose.peer-reviewe

    Towards an Adaptive Skeleton Framework for Performance Portability

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    The proliferation of widely available, but very different, parallel architectures makes the ability to deliver good parallel performance on a range of architectures, or performance portability, highly desirable. Irregularly-parallel problems, where the number and size of tasks is unpredictable, are particularly challenging and require dynamic coordination. The paper outlines a novel approach to delivering portable parallel performance for irregularly parallel programs. The approach combines declarative parallelism with JIT technology, dynamic scheduling, and dynamic transformation. We present the design of an adaptive skeleton library, with a task graph implementation, JIT trace costing, and adaptive transformations. We outline the architecture of the protoype adaptive skeleton execution framework in Pycket, describing tasks, serialisation, and the current scheduler.We report a preliminary evaluation of the prototype framework using 4 micro-benchmarks and a small case study on two NUMA servers (24 and 96 cores) and a small cluster (17 hosts, 272 cores). Key results include Pycket delivering good sequential performance e.g. almost as fast as C for some benchmarks; good absolute speedups on all architectures (up to 120 on 128 cores for sumEuler); and that the adaptive transformations do improve performance
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