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检索条件"任意字段=Proceedings of the 35th ACM SIGPLAN Conference on Programming Language Design and Implementation"

共 255 条记录，以下是121-130 订阅

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Synthesizing Racy Tests 15

Synthesizing Racy Tests

引用

36th acm sigplan conference on programming language design and implementation

作者： Samak, Malavika Ramanathan, Murali Krishna Jagannathan, Suresh Indian Inst Sci Bangalore 560012 Karnataka India Purdue Univ W Lafayette IN 47907 USA

ISBN: (纸本)9781450334686

Subtle concurrency errors in multithreaded libraries that arise because of incorrect or inadequate synchronization are often difficult to pinpoint precisely using only static techniques. On the other hand, the effectiveness of dynamic race detectors is critically dependent on multithreaded test suites whose execution can be used to identify and trigger races. Usually, such multithreaded tests need to invoke a specific combination of methods with objects involved in the invocations being shared appropriately to expose a race. Without a priori knowledge of the race, construction of such tests can be challenging. In this paper, we present a lightweight and scalable technique for synthesizing precisely these kinds of tests. Given a multithreaded library and a sequential test suite, we describe a fully automated analysis that examines sequential execution traces, and produces as its output a concurrent client program that drives shared objects via library method calls to states conducive for triggering a race. Experimental results on a variety of well-tested Java libraries yield 101 synthesized multithreaded tests in less than four minutes. Analyzing the execution of these tests using an off-the-shelf race detector reveals 187 harmful races, including several previously unreported ones.

关键词： design Reliability Verification Race detection dynamic analysis concurrency

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Featherweight Swift: A Core Calculus for Swift's Type System 13

Featherweight Swift: A Core Calculus for Swift's Type System

引用

13th acm sigplan International conference on Software language Engineering (SLE) part of SPLASH conference

作者： Racordon, Dimitri Buchs, Didier Univ Geneva Dept Comp Sci Geneva Switzerland

ISBN: (纸本)9781450381765

Swift is a modern general-purpose programming language, designed to be a replacement for C-based languages. Although primarily directed at development of applications for Apple's operating systems, Swift's adoption has been growing steadily in other domains, ranging from server-side services to machine learning. this success can be partly attributed to a rich type system that enables the design of safe, fast, and expressive programming interfaces. Unfortunately, this richness comes at the cost of complexity, setting a high entry barrier to exploit Swift's full potential. Furthermore, existing documentation typically only relies on examples, leaving new users with little help to build a deeper understanding of the underlying rules and mechanisms. this paper aims to tackle this issue by laying out the foundations for a formal framework to reason about Swift's type system. We introduce Featherweight Swift, a minimal language stripped of all features not essential to describe its typing rules. Featherweight Swift features classes and protocol inheritance, supports retroactive modeling, and emulates Swift's overriding mechanisms. Yet its formalization fits on a few pages. We present Featherweight Swift's syntax and semantics. We then elaborate on the usability of our framework to reason about Swift's features, future extensions, and implementation by discussing a bug in Swift's compiler, discovered throughout the design of our calculus.

关键词： protocol oriented programming language semantics language calculus type systems swift

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proceedings of the acm sigplan Workshop on Memory Systems Performance and Correctness, MSPC 2013

Proceedings of the ACM SIGPLAN Workshop on Memory Systems Pe...

引用

acm sigplan Workshop on Memory Systems Performance and Correctness, MSPC 2013, co-located with the 34th annual acm sigplan conference on programming language design and implementation, PLDI

ISBN: (纸本)9781450321037

the proceedings contain 12 papers. the topics discussed include: APE: accelerator processor extensions to optimize data-compute co-location;a study of data structures with a deep heap shape;introducing kernel-level page reuse for high performance computing;a low overhead method for recovering unused memory inside regions;software-controlled transparent management of heterogeneous memory resources in virtualized systems;program-centric cost models for locality;a new perspective on processing-in-memory architecture design;a coldness metric for cache optimization;all-window data liveness;software-level scheduling to exploit non-uniformly shared data cache on GPGPU;cache rationing for multicore;and analyzing locality of memory references in GPU architectures.

关键词： Data structures

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LoCal: A language for Programs Operating on Serialized Data 2019

LoCal: A Language for Programs Operating on Serialized Data

引用

40th acm sigplan conference on programming language design and implementation (PLDI) part of acm's Federated Computing Research conference (FCRC)

作者： Vollmer, Michael Koparkar, Chaitanya Rainey, Mike Sakka, Laith Kulkarni, Milind Newton, Ryan R. Indiana Univ Comp Sci Bloomington IN 47405 USA Purdue Univ Elect & Comp Engn W Lafayette IN 47907 USA

ISBN: (纸本)9781450367127

In a typical data-processing program, the representation of data in memory is distinct from its representation in a serialized form on disk. the former has pointers and arbitrary, sparse layout, facilitating easy manipulation by a program, while the latter is packed contiguously, facilitating easy I/O. We propose a language, LoCal, to unify in-memory and serialized formats. LoCal extends a region calculus into a location calculus, employing a type system that tracks the byte-addressed layout of all heap values. We formalize LoCal and prove type safety, and show how LoCal programs can be inferred from unannotated source terms. We transform the existing Gibbon compiler to use LoCal as an intermediate language, with the goal of achieving a balance between code speed and data compactness by introducing just enough indirection into heap layouts, preserving the asymptotic complexity of traditional representations, but working with mostly or completely serialized data. We show that our approach yields significant performance improvement over prior approaches to operating on packed data, without abandoning idiomatic programming with recursive functions.

关键词： Region Calculus Compiler Optimization Data Encoding Tree Traversal

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Using role components to implement collaboration-based designs 11

Using role components to implement collaboration-based desig...

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proceedings of the 1996 conference on Object-Oriented programming Systems, languages & Applications

作者： VanHilst, Michael Notkin, David Univ of Washington Seattle United States

ISBN: (纸本)089791788X

In this paper we present a method of code implementation that works in conjunction with collaboration and responsibility based analysis modeling techniques to achieve better code reuse and resilience to change. Our approach maintains a closer mapping from responsibilities in the analysis model to entities in the implementation. In so doing, it leverages the features of flexible design and design reuse found in collaboration-based design models to provide similar adaptability and reuse in the implementation. Our approach requires no special development tools and uses only standard features available in the C++ language. In an earlier paper we described the basic mechanisms used by our approach and discussed its advantages in comparison to the framework approach. In this paper we show how our approach combines code and design reuse, describing specific techniques that can be used in the development of larger applications.

关键词： Object oriented programming

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A General Path-Based Representation for Predicting Program Properties 2018

A General Path-Based Representation for Predicting Program P...

引用

39th acm sigplan conference on programming language design and implementation (PLDI)

作者： Alon, Uri Zilberstein, Meital Levy, Omer Yahav, Eran Technion Haifa Israel Univ Washington Seattle WA 98195 USA

ISBN: (纸本)9781450356985

Predicting program properties such as names or expression types has a wide range of applications. It can ease the task of programming, and increase programmer productivity. A major challenge when learning from programs is how to represent programs in a way that facilitates effective learning. We present a general path-based representation for learning from programs. Our representation is purely syntactic and extracted automatically. the main idea is to represent a program using paths in its abstract syntax tree (AST). this allows a learning model to leverage the structured nature of code rather than treating it as a flat sequence of tokens. We showthat this representation is general and can: (i) cover different prediction tasks, (ii) drive different learning algorithms (for both generative and discriminative models), and (iii) work across different programming languages. We evaluate our approach on the tasks of predicting variable names, method names, and full types. We use our representation to drive both CRF-based and word2vec-based learning, for programs of four languages: JavaScript, Java, Python and C#. Our evaluation shows that our approach obtains better results than task-specific handcrafted representations across different tasks and programming languages.

关键词： programming languages Big Code Machine Learning Learning Representations

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TRANSIT: Specifying Protocols with Concolic Snippets

TRANSIT: Specifying Protocols with Concolic Snippets

引用

34th acm sigplan conference on programming language design and implementation (PLDI)

作者： Udupa, Abhishek Raghavan, Arun Deshmukh, Jyotirmoy V. Mador-Haim, Sela Martin, Milo M. K. Alur, Rajeev Univ Penn Philadelphia PA 19104 USA

ISBN: (纸本)9781450320146

With the maturing of technology for model checking and constraint solving, there is an emerging opportunity to develop programming tools that can transform the way systems are specified. In this paper, we propose a new way to program distributed protocols using concolic snippets. Concolic snippets are sample execution fragments that contain both concrete and symbolic values. the proposed approach allows the programmer to describe the desired system partially using the traditional model of communicating extended finite-state-machines (EFSM), along with high-level invariants and concrete execution fragments. Our synthesis engine completes an EFSM skeleton by inferring guards and updates from the given fragments which is then automatically analyzed using a model checker with respect to the desired invariants. the counterexamples produced by the model checker can then be used by the programmer to add new concrete execution fragments that describe the correct behavior in the specific scenario corresponding to the counterexample. We describe TRANSIT, a language and prototype implementation of the proposed specification methodology for distributed protocols. Experimental evaluations of TRANSIT to specify cache coherence protocols show that (1) the algorithm for expression inference from concolic snippets can synthesize expressions of size 15 involving typical operators over commonly occurring types, (2) for a classical directory-based protocol, TRANSIT automatically generates, in a few seconds, a complete implementation from a specification consisting of the EFSM structure and a few concrete examples for every transition, and (3) a published partial description of the SGI Origin cache coherence protocol maps directly to symbolic examples and leads to a complete implementation in a few iterations, with the programmer correcting counterexamples resulting from underspecified transitions by adding concrete examples in each iteration.

关键词： Program Synthesis Distributed Protocol Synthesis Cache Coherence Protocols programming by Example

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Lightweight, Flexible Object-Oriented Generics 15

Lightweight, Flexible Object-Oriented Generics

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36th acm sigplan conference on programming language design and implementation

作者： Zhang, Yizhou Loring, Matthew C. Salvaneschi, Guido Liskov, Barbara Myers, Andrew C. Cornell Univ Ithaca NY 14853 USA Tech Univ Darmstadt Darmstadt Germany MIT Cambridge MA 02139 USA

ISBN: (纸本)9781450334686

the support for generic programming in modern object-oriented programming languages is awkward and lacks desirable expressive power. We introduce an expressive genericity mechanism that adds expressive power and strengthens static checking, while remaining lightweight and simple in common use cases. Like type classes and concepts, the mechanism allows existing types to model type constraints retroactively. For expressive power, we expose models as named constructs that can be defined and selected explicitly to witness constraints;in common uses of genericity, however, types implicitly witness constraints without additional programmer effort. Models are integrated into the object-oriented style, with features like model generics, model-dependent types, model enrichment, model multimethods, constraint entailment, model inheritance, and existential quantification further extending expressive power in an object-oriented setting. We introduce the new genericity features and show that common generic programming idioms, including current generic libraries, can be expressed more precisely and concisely. the static semantics of the mechanism and a proof of a key decidability property can be found in an associated technical report.

关键词： Genus generic programming constraints models

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Latte: A language, Compiler, and Runtime for Elegant and Efficient Deep Neural Networks 16

Latte: A Language, Compiler, and Runtime for Elegant and Eff...

引用

37th acm sigplan conference on programming language design and implementation

作者： Truong, Leonard Barik, Rajkishore Totoni, Ehsan Liu, Hai Markley, Chick Fox, Armando Shpeisman, Tatiana Univ Calif Berkeley Intel Labs Berkeley CA USA Intel Labs Berkeley CA USA Univ Calif Berkeley Berkeley CA USA

ISBN: (纸本)9781450342612

Deep neural networks (DNNs) have undergone a surge in popularity with consistent advances in the state of the art for tasks including image recognition, natural language processing, and speech recognition. the computationally expensive nature of these networks has led to the proliferation of implementations that sacrifice abstraction for high performance. In this paper, we present Latte, a domain-specific language for DNNs that provides a natural abstraction for specifying new layers without sacrificing performance. Users of Latte express DNNs as ensembles of neurons with connections between them. the Latte compiler synthesizes a program based on the user specification, applies a suite of domain-specific and general optimizations, and emits efficient machine code for heterogeneous architectures. Latte also includes a communication runtime for distributed memory data-parallelism. Using networks described using Latte, we demonstrate 3-6x speedup over Caffe (C++/MKL) on the three state-of-the-art ImageNet models executing on an Intel Xeon E5-2699 v3 x86 CPU.

关键词： Deep Learning Neural Networks Domain Specific language Compiler Optimization

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Polyhedral Auto-transformation with No Integer Linear programming 2018

Polyhedral Auto-transformation with No Integer Linear Progra...

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39th acm sigplan conference on programming language design and implementation (PLDI)

作者： Acharya, Aravind Bondhugula, Uday Cohen, Albert Indian Inst Sci Dept Comp Sci & Automat Bangalore Karnataka India INRIA Paris France DI Ecole Normale Super Paris France

ISBN: (纸本)9781450356985

State-of-the-art algorithms used in automatic polyhedral transformation for parallelization and locality optimization typically rely on Integer Linear programming (ILP). this poses a scalability issue when scaling to tens or hundreds of statements, and may be disconcerting in production compiler settings. In this work, we consider relaxing integrality in the ILP formulation of the Pluto algorithm, a popular algorithm used to find good affine transformations. We show that the rational solutions obtained from the relaxed LP formulation can easily be scaled to valid integral ones to obtain desired solutions, although with some caveats. We first present formal results connecting the solution of the relaxed LP to the original Pluto ILP. We then show that there are difficulties in realizing the above theoretical results in practice, and propose an alternate approach to overcome those while still leveraging linear programming. Our new approach obtains dramatic compile-time speedups for a range of large benchmarks. While achieving these compile-time improvements, we show that the performance of the transformed code is not sacrificed. Our approach to automatic transformation provides a mean compilation time improvement of 5.6x over state-of-the-art on relevant challenging benchmarks from the NAS PB, SPEC CPU 2006, and PolyBench suites. We also came across situations where prior frameworks failed to find a transformation in a reasonable amount of time, while our new approach did so instantaneously.

关键词： Polyhedral transformation Pluto algorithm

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