SHF: Medium: Human-Centric Program Synthesis

SHF:媒介:以人为本的程序综合

基本信息

  • 批准号:
    2107397
  • 负责人:
  • 金额:
    $ 100万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2021
  • 资助国家:
    美国
  • 起止时间:
    2021-09-01 至 2025-08-31
  • 项目状态:
    未结题

项目摘要

The goal of Program Synthesis is to automate the process of software development, helping to build software faster, cheaper, and with fewer errors. Despite many recent research advances in this area, there is limited to no use of synthesis in mainstream software development. The reason is that prior research in this area has mainly focused on the algorithms that power program synthesizers, and have devoted much less attention to the interaction between a synthesizer and a human programmer. This project investigates the human-facing side of Program Synthesis, with the goal of making synthesizers more usable by programmers and integrating these tools better into software-development workflows. By transforming the way in which programmers write code, this project has the potential to make software better at a lower cost.The project explores three broad research arcs at the intersection of Program Synthesis and Human-Computer Interaction. (1) Communicating Intent: How should the programmer provide input to the synthesizer? (2) Comprehending Synthesized Code: How should the programmer understand the output of the synthesizer? (3) Tightly Integrated Synthesis Workflow: How should we tightly integrate synthesis into the programmer's workflow? More specifically, the investigators tackle the following research challenges: (1) understanding how synthesis techniques can take advantage of multiples kinds of specifications; (2) developing novel synthesis techniques that can work in the face of incomplete or incorrect specifications; (3) guiding synthesis techniques to take into account human-oriented considerations, such as understandability of the code, or predictability of the tool; (4) personalize synthesis approaches to the preferences of the programmer, to make the tools more usable and the results more understandable to the individual programmer; (5) adapting traditional programming workflows to make them more amenable to synthesis; (6) making it easier for the programmer to decide, given a task, if they should use synthesis or just write the code directly. All new techniques developed in this project are incorporated into an online development environment Snippy, which is freely available on the web. To evaluate Snippy, the investigators conduct controlled A-B experiments with programmers, testing whether Snippy helps them solve typical programming tasks.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
程序合成的目标是使软件开发过程自动化,帮助更快、更便宜、错误更少地构建软件。尽管在这一领域有许多最新的研究进展,但在主流软件开发中,合成的使用是有限的。原因在于,这一领域的先前研究主要集中在为程序合成器提供动力的算法上,而对合成器和人类程序员之间的交互关注得少得多。该项目研究了程序合成的人性化方面,目标是使程序员更好地使用合成器,并将这些工具更好地集成到软件开发工作流程中。通过改变程序员编写代码的方式,该项目有可能以较低的成本使软件更好。该项目探索了程序合成和人机交互交叉点的三个广泛的研究领域。(1)交流意图:程序员应该如何向合成器提供输入?(2)理解合成代码:程序员应该如何理解合成器的输出?(3)紧密集成的合成工作流程:我们应该如何将合成紧密集成到程序员的工作流程中?更具体地说,研究人员解决了以下研究挑战:(1)理解合成技术如何利用多种规格;(2)开发新的合成技术,可以在不完整或不正确的规格面前工作;(3)指导合成技术考虑到以人为本的考虑因素,如代码的可理解性,或工具的可预测性;(4)开发新的合成技术。(4)根据程序员的偏好个性化综合方法,使工具更可用,结果更容易被程序员个人理解;(5)调整传统的编程工作流程,使其更适合综合;(6)使程序员更容易决定,给定任务,他们应该使用综合还是直接编写代码。在这个项目中开发的所有新技术都集成到一个在线开发环境Snippy中,该环境可以在网络上免费获得。为了对Snippy进行评估,研究人员对程序员进行了受控的A-B实验,测试Snippy是否帮助他们解决了典型的编程任务。该奖项反映了NSF的法定使命,并通过使用基金会的智力价值和更广泛的影响审查标准进行评估,被认为值得支持。

项目成果

期刊论文数量(2)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Grounded Copilot: How Programmers Interact with Code-Generating Models
LooPy: interactive program synthesis with control structures
LooPy:具有控制结构的交互式程序合成
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Nadia Polikarpova其他文献

Laurel: Generating Dafny Assertions Using Large Language Models
Laurel:使用大型语言模型生成 Dafny 断言
  • DOI:
    10.48550/arxiv.2405.16792
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Eric Mugnier;Emmanuel Anaya Gonzalez;Ranjit Jhala;Nadia Polikarpova;Yuanyuan Zhou
  • 通讯作者:
    Yuanyuan Zhou
HYSYNTH: Context-Free LLM Approximation for Guiding Program Synthesis
HYSYNTH:用于指导程序综合的上下文无关 LLM 近似
  • DOI:
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Shraddha Barke;Emmanuel Anaya Gonzalez;Saketh Ram Kasibatla;Taylor Berg;Nadia Polikarpova
  • 通讯作者:
    Nadia Polikarpova

Nadia Polikarpova的其他文献

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{{ truncateString('Nadia Polikarpova', 18)}}的其他基金

CAREER: Type-Driven Program Synthesis
职业:类型驱动程序综合
  • 批准号:
    1943623
  • 财政年份:
    2020
  • 资助金额:
    $ 100万
  • 项目类别:
    Continuing Grant
SHF: Small: NSF-BSF: Synthesis of Safe Pointer-Manipulating Programs
SHF:小:NSF-BSF:安全指针操作程序的综合
  • 批准号:
    1911149
  • 财政年份:
    2019
  • 资助金额:
    $ 100万
  • 项目类别:
    Standard Grant
SHF: Small: Collaborative Research: Resource-Guided Program Synthesis
SHF:小型:协作研究:资源引导程序综合
  • 批准号:
    1814358
  • 财政年份:
    2018
  • 资助金额:
    $ 100万
  • 项目类别:
    Standard Grant

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