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检索条件"任意字段=Proceedings of the ACM SIGPLAN 1993 conference on Programming language design and implementation"

共 1231 条记录，以下是41-50 订阅

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CGP++ : A Modern C++ implementation of Cartesian Genetic programming

CGP++ : A Modern C++ Implementation of Cartesian Genetic Pro...

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2024 Genetic and Evolutionary Computation conference, GECCO 2024

作者： Kalkreuth, Roman Baeck, Thomas CNRS LIP6 Sorbonne Université Paris France LIACS Leiden University Leiden Netherlands

ISBN: (纸本)9798400704949

The reference implementation of Cartesian Genetic programming (CGP) was written in the C programming language. C inherently follows a procedural programming paradigm, which entails challenges in providing a reusable and scalable implementation model for complex structures and methods. Moreover, due to the limiting factors of C, the reference implementation of CGP does not provide a generic framework and is therefore restricted to a set of predefined evaluation types. Besides the reference implementation, we also observe that other existing implementations are limited with respect to the features provided. In this work, we therefore propose the first version of a modern C++ implementation of CGP that pursues object-oriented design and generic programming paradigm to provide an efficient implementation model that can facilitate the discovery of new problem domains and the implementation of complex advanced methods that have been proposed for CGP over time. With the proposal of our new implementation, we aim to generally promote interpretability, accessibility and reproducibility in the field of CGP. © 2024 Copyright is held by the owner/author(s). Publication rights licensed to acm.

关键词： Genetic programming

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ADA: a tool for visualizing the architectural overview of open-source repositories 11

ADA: a tool for visualizing the architectural overview of op...

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11th acm sigplan International Workshop on the State Of the Art in Program Analysis, SOAP 2022, co-located with the 43rd acm sigplan International conference on programming language design and implementation, PLDI 2022

作者： Misu, Md Rakib Hossain Janjanin, Aleksandar Saša Bian, Zhiqiang Burlacu, Valentin-Sebastian Anteski, Naum University College London United Kingdom

ISBN: (纸本)9781450392747

Writing highly maintainable and efficient software code is becoming increasingly difficult, especially while following the rapid, agile development process and working in a distributed team. One of the key indicators of that inefficient software design is a high degree of code coupling, which leads to unwanted side-effects during refactoring and acts as a burden during future development. To alleviate these problems, we developed a visualization tool, ADA, that statically analyzes an open-source repository and seeks to address the issue of code coupling by providing developers with a powerful graphic representation. ADA showcases the relationships and the degree of inter-connectivity between the classes. ADA will ultimately guide developers to instantly locate the coupled area and assist them in decoupling it. © 2022 acm.

关键词： Software design

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Towards an implementation of differential dynamic logic in PVS 11

Towards an implementation of differential dynamic logic in P...

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作者： Slagel, J. Tanner Muñoz, César Balachandran, Swee Moscato, Mariano Dutle, Aaron Masci, Paolo White, Lauren Nasa Langley Research Center United States National Institute of Aerospace United States

ISBN: (纸本)9781450392747

This paper describes an ongoing effort to embed and verify differential dynamic logic (dL) in the Prototype Verification System (PVS). dL is a logic for specifying and formally reasoning about hybrid systems, i.e., systems that employ both continuous and discrete dynamics. There are several benefits of this effort. First, the embedding of dL in PVS offers an independent formal verification of the semantics and inference rules of dL. Second, the embedding is fully operational within PVS, giving PVS practitioners the ability to use dL in the formal specification and verification of hybrid systems. Third, the rich specification language, type system, and powerful interactive prover of PVS can be used on dL objects. In addition to the embedding and verification of dL, a custom extension for Visual Studio Code has been developed, so that a stylized dL syntax can be used to specify hybrid programs and their properties. © 2022 acm.

关键词： Hybrid systems

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proceedings - 2024 32nd IEEE/acm International conference on Program Comprehension, ICPC 2024

Proceedings - 2024 32nd IEEE/ACM International Conference on...

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32nd IEEE/acm International conference on Program Comprehension, ICPC 2024

ISBN: (纸本)9798400705861

The proceedings contain 46 papers. The topics discussed include: exploring and improving code completion for test code;on the generalizability of deep learning-based code completion across programming language versions;ESGen: commit message generation based on edit sequence of code change;capturing and understanding the drift between design, implementation, and documentation;towards summarizing code snippets using pre-trained transformers;improving AST-level code completion with graph retrieval and multi-field attention;HyperCRX: a browser extension for insights into GitHub projects and developers;innovating coding: evaluating the impact of innovative thinking in programming;and MESIA: understanding and leveraging supplementary nature of method-level comments for automatic comment generation.

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Ou: Automating the Parallelization of Zero-Knowledge Protocols 23

Ou: Automating the Parallelization of Zero-Knowledge Protoco...

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30th acm SIGSAC conference on Computer and Communications Security (acm CCS)

作者： Sang, Yuyang Luo, Ning Judson, Samuel Chaimberg, Ben Antonopoulos, Timos Wang, Xiao Piskac, Ruzica Shao, Zhong Yale Univ New Haven CT 06520 USA Northwestern Univ Evanston IL USA

ISBN: (纸本)9798400700507

A zero-knowledge proof (ZKP) is a powerful cryptographic primitive used in many decentralized or privacy-focused applications. However, the high overhead of ZKPs can restrict their practical applicability. We design a programming language, Ou, aimed at easing the programmer's burden when writing efficient ZKPs, and a compiler framework, Lian, that automates the analysis and distribution of statements to a computing cluster. Lian uses programming language semantics, formal methods, and combinatorial optimization to automatically partition an Ou program into efficiently sized chunks for parallel ZK-proving and/or verification. We contribute: (1) A front-end language where users can write proof statements as imperative programs in a familiar syntax;(2) A compiler architecture and implementation that automatically analyzes the program and compiles it into an optimized IR that can be lifted to a variety of ZKP constructions;and (3) A cutting algorithm, based on Pseudo-Boolean optimization and Integer Linear programming, that reorders instructions and then partitions the program into efficiently sized chunks for parallel evaluation and efficient state reconciliation.

关键词： programming language Zero-knowledge proofs Parallelization

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proceedings of the acm sigplan conference on programming language design and implementation (PLDI)

Proceedings of the ACM SIGPLAN Conference on Programming Lan...

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38th acm sigplan conference on programming language design and implementation, PLDI 2017

ISBN: (纸本)9781450349888

The proceedings contain 47 papers. The topics discussed include: cache locality optimization for recursive programs;generalizations of the theory and deployment of triangular inequality for compiler-based strength reduction;DemoMatch: API discovery from demonstrations;similarity of binaries through re-optimization;BARRACUDA: binary-level analysis of runtime races in CUDA programs;bringing the web up to speed with WebAssembly;proactive and adaptive energy-aware programming with mixed typechecking;simple, fast, and safe manual memory management;efficient and precise points-to analysis: modeling the heap by merging equivalent automata;static deadlock detection for asynchronous c# programs;achieving high coverage for floating-point code via unconstrained programming;skeletal program enumeration for rigorous compiler testing;decomposition instead of self-composition for proving the absence of timing channels;automatic program inversion using symbolic transducers;rigorous analysis of software countermeasures against cache attacks;component-based synthesis of table consolidation and transformation tasks from examples;and network configuration synthesis with abstract topologies.

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Compiling Stan to Generative Probabilistic languages and Extension to Deep Probabilistic programming 2021

Compiling Stan to Generative Probabilistic Languages and Ext...

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42nd acm sigplan International conference on programming language design and implementation (PLDI)

作者： Baudart, Guillaume Burroni, Javier Hirzel, Martin Mandel, Louis Shinnar, Avraham PSL Univ Ecole Normale Super INRIA Paris Paris France UMass Amherst Amherst MA USA IBM Res MIT IBM Watson AI Lab Armonk NY USA

ISBN: (纸本)9781450383912

Stan is a probabilistic programming language that is popular in the statistics community, with a high-level syntax for expressing probabilistic models. Stan differs by nature from generative probabilistic programming languages like Church, Anglican, or Pyro. This paper presents a comprehensive compilation scheme to compile any Stan model to a generative language and proves its correctness. We use our compilation scheme to build two new backends for the Stanc3 compiler targeting Pyro and NumPyro. Experimental results show that the NumPyro backend yields a 2.3x speedup compared to Stan in geometric mean over 26 benchmarks. Building on Pyro we extend Stan with support for explicit variational inference guides and deep probabilistic models. That way, users familiar with Stan get access to new features without having to learn a fundamentally new language.

关键词： Probabilistic programming Semantics Stan Pyro

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ProSE: The Architecture and design of a Protein Discovery Engine 27

ProSE: The Architecture and Design of a Protein Discovery En...

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27th acm International conference on Architectural Support for programming languages and Operating Systems (ASPLOS)

作者： Robson, Eyes Xu, Ceyu Wills, Lisa Wu Univ Calif Berkeley Berkeley CA 94720 USA Duke Univ Durham NC USA

ISBN: (纸本)9781450392051

Protein language models have enabled breakthrough approaches to protein structure prediction, function annotation, and drug discovery. A primary limitation to the widespread adoption of these powerful models is the high computational cost associated with the training and inference of these models, especially at longer sequence lengths. We present the architecture, microarchitecture, and hardware implementation of a protein design and discovery accelerator, ProSE (Protein Systolic Engine). ProSE has a collection of custom heterogeneous systolic arrays and special functions that process transfer learning model inferences efficiently. The architecture marries SIMD-style computations with systolic array architectures, optimizing coarse-grained operation sequences across model layers to achieve efficiency without sacrificing generality. ProSE performs Protein BERT inference at up to 6.9x speedup and 48x power efficiency (performance/Watt) compared to one NVIDIA A100 GPU. ProSE achieves up to 5.5 x (12.7x) speedup and 173x (249x) power efficiency compared to TPUv3 (TPUv2).

关键词： Accelerators Neural Networks Transformers Domain-Specific Architecture NLP Protein design

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JAX Based Parallel Inference for Reactive Probabilistic programming 2022

JAX Based Parallel Inference for Reactive Probabilistic Prog...

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23rd International conference on languages, Compilers, and Tools for Embedded System (LCTES)

作者： Baudart, Guillaume Mandel, Louis Tekin, Reyyan PSL Univ DI ENS Ecole Normale Super CNRSInria Paris France IBM Res Armonk NY USA

ISBN: (纸本)9781450392662

ProbZelus is a synchronous probabilistic language for the design of reactive probabilistic models in interaction with an environment. Reactive inference methods continuously learn distributions over the unobserved parameters of the model from statistical observations. Unfortunately, this inference problem is in general intractable. Monte Carlo inference techniques thus rely on many independent executions to compute accurate approximations. These methods are expensive but can be parallelized. We propose to use JAX to parallelize ProbZelus reactive inference engine. JAX is a recent library to compile Python code which can then be executed on massively parallel architectures such as GPUs or TPUs. In this paper, we describe a new reactive inference engine implemented in JAX and the new associated JAX backend for ProbZelus. We show on existing benchmarks that our new parallel implementation outperforms the original sequential implementation for a high number of particles.

关键词： Probabilistic programming Reactive programming Streaming Inference Parallel Computing Compilation

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Ansible Lightspeed: A Code Generation Service for IT Automation 24

Ansible Lightspeed: A Code Generation Service for IT Automat...

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39th acm/IEEE International conference on Automated Software Engineering (ASE)

作者： Sahoo, Priyam Pujar, Saurabh Nalawade, Ganesh Gebhardt, Richard Mandel, Louis Buratti, Luca Red Hat Raleigh NC USA IBM Res Yorktown Hts NY 10598 USA

ISBN: (数字)9798400712487

ISBN: (纸本)9798400712487

The availability of Large language Models (LLMs) which can generate code, has made it possible to create tools that improve developer productivity. Integrated development environments or IDEs which developers use to write software are often used as an interface to interact with LLMs. Although many such tools have been released, almost all of them focus on general-purpose programming languages. Domain-specific languages, such as those crucial for Information Technology (IT) automation, have not received much attention. Ansible is one such YAML-based IT automation-specific language. Ansible Lightspeed is an LLM-based service designed explicitly to generate Ansible YAML, given natural language prompt. In this paper, we present the design and implementation of the Ansible Lightspeed service. We then evaluate its utility to developers using diverse indicators, including extended utilization, analysis of user edited suggestions, as well as user sentiments analysis. The evaluation is based on data collected for 10,696 real users including 3,910 returning users. The code for Ansible Lightspeed service and the analysis framework is made available for others to use. To our knowledge, our study is the first to involve thousands of users of code assistants for domain-specific languages. We are also the first code completion tool to present N-Day user retention figures, which is 13.66% on Day 30. We propose an improved version of user acceptance rate, called Strong Acceptance rate, where a suggestion is considered accepted only if less than 50% of it is edited and these edits do not change critical parts of the suggestion. By focusing on Ansible, Lightspeed is able to achieve a strong acceptance rate of 49.08% for multi-line Ansible task suggestions. With our findings we provide insights into the effectiveness of small, dedicated models in a domain-specific context. We hope this work serves as a reference for software engineering and machine learning researchers exploring code c

关键词： Productivity Sentiment analysis Codes Automation Large language models Natural languages Machine learning Software Software engineering Domain specific languages

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