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检索条件"任意字段=36th ACM SIGPLAN Conference on Programming Language Design and Implementation"

共 320 条记录，以下是171-180 订阅

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CLAP: Recording Local Executions to Reproduce Concurrency Failures

CLAP: Recording Local Executions to Reproduce Concurrency Fa...

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

作者： Huang, Jeff Zhang, Charles Dolby, Julian Hong Kong Univ Sci & Technol Hong Kong Hong Kong Peoples R China

ISBN: (纸本)9781450320146

We present CLAP, a new technique to reproduce concurrency bugs. CLAP has two key steps. First, it logs thread local execution paths at runtime. Second, offline, it computes memory dependencies that accord with the logged execution and are able to reproduce the observed bug. the second step works by combining constraints from the thread paths and constraints based on a memory model, and computing an execution with a constraint solver. CLAP has four major advantages. First, logging purely local execution of each thread is substantially cheaper than logging memory interactions, which enables CLAP to be efficient compared to previous approaches. Second, our logging does not require any synchronization and hence with no added memory barriers or fences;this minimizes perturbation and missed bugs due to extra synchronizations foreclosing certain racy behaviors. third, since it uses no synchronization, we extend CLAP to work on a range of relaxed memory models, such as TSO and PSO, in addition to sequential consistency. Fourth, CLAP can compute a much simpler execution than the original one, that reveals the bug with minimal thread context switches. To mitigate the scalability issues, we also present an approach to parallelize constraint solving, which theoretically scales our technique to programs with arbitrary execution length. Experimental results on a variety of multithreaded benchmarks and real world concurrent applications validate these advantages by showing that our technique is effective in reproducing concurrency bugs even under relaxed memory models;furthermore, it is significantly more efficient than a state-of-the-art technique that records shared memory dependencies, reducing execution time overhead by 45% and log size by 88% on average.

关键词： Algorithms design Performance theory Concurrency Bug Reproduction Local Execution Constraint Solving

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SPL^LIFT - Statically Analyzing Software Product Lines in Minutes Instead of Years 13

SPL<SUP>LIFT</SUP> - Statically Analyzing Software Product L...

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

作者： Bodden, Eric Toledo, Tarsis Ribeiro, Marcio Brabrand, Claus Borba, Paulo Mezini, Mira Tech Univ Darmstadt EC SPRIDE Darmstadt Germany IT Univ Copenhagen Copenhagen Denmark Univ Fed Pernambuco Recife PE Brazil Univ Fed Alagoas Maceio Brazil

ISBN: (纸本)9781450320146

A software product line (SPL) encodes a potentially large variety of software products as variants of some common code base. Up until now, re-using traditional static analyses for SPLs was virtually intractable, as it required programmers to generate and analyze all products individually. In this work, however, we show how an important class of existing inter-procedural static analyses can be transparently lifted to SPLs. Without requiring programmers to change a single line of code, our approach SPLLIFT automatically converts any analysis formulated for traditional programs within the popular IFDS framework for inter-procedural, finite, distributive, subset problems to an SPL-aware analysis formulated in the IDE framework, a well-known extension to IFDS. Using a full implementation based on Heros, Soot, CIDE and JavaBDD, we show that with SPLLIFT one can reuse IFDS-based analyses without changing a single line of code. through experiments using three static analyses applied to four Java-based product lines, we were able to show that our approach produces correct results and outperforms the traditional approach by several orders of magnitude.

关键词： Software product lines inter-procedural static analysis context sensitive flow sensitive design languages Performance

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language requirements for large-scale generic libraries 05

Language requirements for large-scale generic libraries

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4th International conference on Generative programming and Component Engineering

作者： Siek, J Lumsdaine, A Indiana Univ Open Syst Lab Bloomington IN 47405 USA

ISBN: (纸本)3540291385

the past decade of experience has demonstrated that the generic programming methodology is highly effective for the design, implementation, and use of large-scale software libraries. the fundamental principle of generic programming is the realization of interfaces for entire sets of components, based on their essential syntactic and semantic requirements, rather than for any particular components. Many programming languages have features for describing interfaces between software components, but none completely support the approach used in generic programming. We have recently developed G, a language designed to provide first-class language support for generic programming and large-scale libraries. In this paper, we present an overview of g and analyze the interdependence between language features and library design in light of a complete implementation of the Standard Template Library using G. In addition, we discuss important issues related to modularity and encapsulation in large-scale libraries and how language support for validation of components in isolation can prevent many common problems in component integration.

关键词： Digital libraries

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signatr: A Data-Driven Fuzzing Tool for R 15

signatr: A Data-Driven Fuzzing Tool for R

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15th International conference on Software language Engineering (SLE)

作者： Turcotte, Alexi Donat-Bouillud, Pierre Krikava, Filip Vitek, Jan Northeastern Univ Boston MA 02115 USA Czech Tech Univ Prague Czech Republic

ISBN: (纸本)9781450399197

the fast-and-loose, permissive semantics of dynamic programming languages limit the power of static analyses. For that reason, soundness is often traded for precision through dynamic program analysis. Dynamic analysis is only as good as the available runnable code, and relying solely on test suites is fraught as they do not cover the full gamut of possible behaviors. Fuzzing is an approach for automatically exercising code, and could be used to obtain more runnable code. However, the shape of user-defined data in dynamic languages is difficult to intuit, limiting a fuzzer's reach. We propose a feedback-driven blackbox fuzzing approach which draws inputs from a database of values recorded from existing code. We implement this approach in a tool called signatr for the R language. We present the insights of its design and implementation, and assess signatr's ability to uncover new behaviors by fuzzing 4,829 R functions from 100 R packages, revealing 1,195,184 new signatures.

关键词： R fuzzing dynamic program analysis dynamic programming languages

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Improving on the Experience of Hand-Assembling Programs for Application-Specific Architectures 21

Improving on the Experience of Hand-Assembling Programs for ...

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5th International conference on the Art, Science, and Engineering of programming (programming)

作者： Piumarta, Ian Kyoto Univ Adv Sci Kyoto Japan

ISBN: (纸本)9781450389860

Creating an application-specific processor is an effective and popular way to solve many problems in embedded hardware design using FPGAs, ASICs, or custom silicon. programming these processors is complicated by the lack of toolchain support for creating the necessary binary code as part of hardware design, implementation, and evaluation. Hardware developers who cannot create their own ad-hoc assembler are left to hand-assemble their code into binary instructions which is both painful and error prone. We present a tool that supports the rapid creation of assemblers for application-specific processors. A single language is used to specify both instruction formats as collections of bit fields and the instantiation of those formats into sequences of binary instructions as a single, homogeneous activity that is designed to be as familiar and accessible to hardware designers as possible. the output from the tool can be used directly by hardware synthesis tools to initialise the program memory of an application-specific processor.

关键词： domain specific languages macro languages micro assemblers microcode embedded programming application specific processor implementation FPGA configuration memory

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Green-Marl: A DSL for Easy and Efficient Graph Analysis

Green-Marl: A DSL for Easy and Efficient Graph Analysis

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17th International conference on Architectural Support for programming languages and Operating Systems

作者： Hong, Sungpack Chafi, Hassan Sedlar, Eric Olukotun, Kunle Stanford Univ Pervas Parallelism Lab Stanford CA 94305 USA

ISBN: (纸本)9781450307598

the increasing importance of graph-data based applications is fueling the need for highly efficient and parallel implementations of graph analysis software. In this paper we describe Green-Marl, a domain-specific language (DSL) whose high level language constructs allow developers to describe their graph analysis algorithms intuitively, but expose the data-level parallelism inherent in the algorithms. We also present our Green-Marl compiler which translates high-level algorithmic description written in Green-Marl into an efficient C++ implementation by exploiting this exposed data-level parallelism. Furthermore, our Green-Marl compiler applies a set of optimizations that take advantage of the high-level semantic knowledge encoded in the Green-Marl DSL. We demonstrate that graph analysis algorithms can be written very intuitively with Green-Marl through some examples, and our experimental results show that the compiler-generated implementation out of such descriptions performs as well as or better than highly-tuned handcoded implementations.

关键词： Algorithms design Performance Graph Domain-Specific language Parallel programming

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MORBIG: A Static Parser for POSIX Shell 11

MORBIG: A Static Parser for POSIX Shell

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11th acm sigplan International conference on Software language Engineering (SLE) part of SPLASH conference

作者： Regis-Gianas, Yann Jeannerod, Nicolas Treinen, Ralf Univ Paris Diderot CNRS INRIA IRIFPI R2 Paris France Univ Paris Diderot CNRS IRIF Ecole Normale Super Paris France Univ Paris Diderot CNRS IRIF Paris France

ISBN: (纸本)9781450360296

the POSIX shell language defies conventional wisdom of compiler construction on several levels: the shell language was not designed for static parsing, but with an intertwining of syntactic analysis and execution by expansion in mind. Token recognition cannot be specified by regular expressions, lexical analysis depends on the parsing context and the evaluation context, and the shell grammar given in the specification is ambiguous. Besides, the unorthodox design choices of the shell language fit badly in the usual specification languages used to describe other programming languages. this makes the standard usage of LEX and YACC as a pipeline inadequate for the implementation of a parser for POSIX shell. the existing implementations of shell parsers are complex and use low-level character-level parsing code which is difficult to relate to the POSIX specification. We find it hard to trust such parsers, especially when using them for writing automatic verification tools for shell scripts. this paper offers an overview of the technical difficulties related to the syntactic analysis of the POSIX shell language. It also describes how we have resolved these difficulties using advanced parsing techniques (namely speculative parsing, parser state introspection, context-dependent lexical analysis and longest-prefix parsing) while keeping the implementation at a sufficiently high level of abstraction so that experts can check that the POSIX standard is respected. the resulting tool, called MORBIG, is an open-source static parser for a well-defined and realistic subset of the POSIX shell language.

关键词： Parsing POSIX shell functional programming

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Input Responsiveness: Using Canary Inputs to Dynamically Steer Approximation 16

Input Responsiveness: Using Canary Inputs to Dynamically Ste...

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37th acm sigplan conference on programming language design and implementation

作者： Laurenzano, Michael A. Hill, Parker Samadi, Mehrzad Mahlke, Scott Mars, Jason Tang, Lingjia Univ Michigan Dept Elect Engn & Comp Sci Ann Arbor MI 48109 USA

ISBN: (纸本)9781450342612

this paper introduces Input Responsive Approximation ( IRA), an approach that uses a canary input - a small program input carefully constructed to capture the intrinsic properties of the original input - to automatically control how program approximation is applied on an input-by-input basis. Motivating this approach is the observation that many of the prior techniques focusing on choosing how to approximate arrive at conservative decisions by discounting substantial differences between inputs when applying approximation. the main challenges in overcoming this limitation lie in making the choice of how to approximate both effectively (e.g., the fastest approximation that meets a particular accuracy target) and rapidly for every input. With IRA, each time the approximate program is run, a canary input is constructed and used dynamically to quickly test a spectrum of approximation alternatives. Based on these runtime tests, the approximation that best fits the desired accuracy constraints is selected and applied to the full input to produce an approximate result. We use IRA to select and parameterize mixes of four approximation techniques from the literature for a range of 13 image processing, machine learning, and data mining applications. Our results demonstrate that IRA significantly outperforms prior approaches, delivering an average of 10.2x speedup over exact execution while minimizing accuracy losses in program outputs.

关键词： Performance Runtime Systems Compilers Approximate Computing Performance Experimentation design

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Maximal Sound Predictive Race Detection with Control Flow Abstraction 14

Maximal Sound Predictive Race Detection with Control Flow Ab...

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35th acm sigplan conference on programming language design and implementation (PLDI)

作者： Huang, Jeff Meredith, Patrick O'Neil Rosu, Grigore Univ Illinois Dept Comp Sci Urbana IL 61801 USA

ISBN: (纸本)9781450327848

Despite the numerous static and dynamic program analysis techniques in the literature, data races remain one of the most common bugs in modern concurrent software. Further, the techniques that do exist either have limited detection capability or are unsound, meaning that they report false positives. We present a sound race detection technique that achieves a provably higher detection capability than existing sound techniques. A key insight of our technique is the inclusion of abstracted control flow information into the execution model, which increases the space of the causal model permitted by classical happens-before or causally-precedes based detectors. By encoding the control flow and a minimal set of feasibility constraints as a group of first-order logic formulae, we formulate race detection as a constraint solving problem. Moreover, we formally prove that our formulation achieves the maximal possible detection capability for any sound dynamic race detector with respect to the same input trace under the sequential consistency memory model. We demonstrate via extensive experimentation that our technique detects more races than the other state-of-the-art sound race detection techniques, and that it is scalable to executions of real world concurrent applications with tens of millions of critical events. these experiments also revealed several previously unknown races in real systems (e. g., Eclipse) that have been confirmed or fixed by the developers. Our tool is also adopted by Eclipse developers.

关键词： Algorithms design theory Maximal Sound Data Race Prediction Control Flow

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Expressing and Verifying Probabilistic Assertions 14

Expressing and Verifying Probabilistic Assertions

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35th acm sigplan conference on programming language design and implementation (PLDI)

作者： Sampson, Adrian Panchekha, Pavel Mytkowicz, Todd McKinley, Kathryn S. Grossman, Dan Ceze, Luis Univ Washington Seattle WA 98195 USA

ISBN: (纸本)9781450327848

Traditional assertions express correctness properties that must hold on every program execution. However, many applications have probabilistic outcomes and consequently their correctness properties are also probabilistic (e. g., they identify faces in images, consume sensor data, or run on unreliable hardware). Traditional assertions do not capture these correctness properties. this paper proposes that programmers express probabilistic correctness properties with probabilistic assertions and describes a new probabilistic evaluation approach to efficiently verify these assertions. Probabilistic assertions are Boolean expressions that express the probability that a property will be true in a given execution rather than asserting that the property must always be true. Given either specific inputs or distributions on the input space, probabilistic evaluation verifies probabilistic assertions by first performing distribution extraction to represent the program as a Bayesian network. Probabilistic evaluation then uses statistical properties to simplify this representation to efficiently compute assertion probabilities directly or with sampling. Our approach is a mix of both static and dynamic analysis: distribution extraction statically builds and optimizes the Bayesian network representation and sampling dynamically interprets this representation. We implement our approach in a tool called MAYHAP for C and C++ programs. We evaluate expressiveness, correctness, and performance of MAYHAP on programs that use sensors, perform approximate computation, and obfuscate data for privacy. Our case studies demonstrate that probabilistic assertions describe useful correctness properties and that MAYHAP efficiently verifies them.

关键词： languages Reliability Probabilistic programming approximate computing data obfuscation differential privacy sensors symbolic execution

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