CAREER: Foundations and Applications of Constraint-based Synthesis

职业:基于约束的综合的基础和应用

基本信息

  • 批准号:
    2049911
  • 负责人:
  • 金额:
    $ 52.46万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2021
  • 资助国家:
    美国
  • 起止时间:
    2021-04-01 至 2026-03-31
  • 项目状态:
    未结题

项目摘要

Program synthesis promises to democratize programming for the masses by automating the generation of tedious, error-prone code from more natural and understandable user-provided specification. Over the past two decades, advances in computational power have led to a proliferation of program-synthesis techniques that draw upon various fields ranging from logic, programming-language theory, and machine learning. These techniques differ substantially in how they operate, and no single technique is universally superior in all cases. Furthermore, little is understood about users' actual needs and sentiment towards advanced development tools like synthesizers, which inevitably leads to the development of theoretically interesting but ultimately uncompelling or impractical tools. The novelties of this project are two-fold: (a) providing a unifying framework for these differing techniques so that their theoretical underpinnings can be better understood and next-generation program synthesis tools can be built on top of this framework, and (b) identifying the set of human factors that should be considered when making program-synthesis tools. This project's impact is, ultimately, unifying perspectives on program synthesis not just in terms of techniques but also disciplines: programming languages, human-computing interaction, and computer-science education.The project focuses on two primary efforts. The first is developing a unified set of semantic foundations for synthesis based on a generalized notion of constraint that captures the common forms of specifications found with current techniques, e.g., types, examples, logical constraints, syntactic constraints, and partial programs. This constraint-based approach to synthesis naturally leads to a deductive, hole-guided programming style, different from traditional programming models. Therefore, the project's second effort is a systematic study of the needs and sentiment of developers towards this style of programming and the design of next-generation development tools based on these results.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.
程序合成通过从更自然、更容易理解的用户提供的规范中自动生成繁琐、容易出错的代码,有望使大众编程民主化。在过去的二十年里,计算能力的进步导致了程序合成技术的激增,这些技术利用了从逻辑、编程语言理论到机器学习等各个领域。这些技术在操作方式上有很大的不同,没有一种技术在所有情况下都是普遍优越的。此外,对于用户对高级开发工具(如合成器)的实际需求和情感了解甚少,这不可避免地导致开发理论上有趣但最终不引人注目或不切实际的工具。这个项目的新颖之处在于两个方面:(a)为这些不同的技术提供了一个统一的框架,以便更好地理解它们的理论基础,并可以在此框架之上构建下一代程序合成工具;(b)确定在制作程序合成工具时应考虑的人为因素。这个项目的最终影响是,不仅在技术方面,而且在学科方面统一了程序综合的观点:编程语言、人机交互和计算机科学教育。该项目侧重于两项主要工作。第一个是基于约束的广义概念开发一套统一的语义基础,该概念捕获了当前技术中常见的规范形式,例如,类型、示例、逻辑约束、语法约束和部分程序。这种基于约束的综合方法自然会导致演绎的、孔洞导向的编程风格,这与传统的编程模型不同。因此,该项目的第二次努力是系统地研究开发人员对这种编程风格的需求和情感,并基于这些结果设计下一代开发工具。该奖项反映了美国国家科学基金会的法定使命,并通过使用基金会的知识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(4)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Reactamole: Functional Reactive Molecular Programming
Reactamole:功能反应分子编程
Snowflake: Supporting Programming and Proofs
Snowflake:支持编程和证明
Notional Machine in Mathematics and Introductory Computer Science Courses
数学和计算机科学入门课程中的概念机
Verifying Chemical Reaction Networks with the Isabelle Theorem Prover
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Peter-Michael Osera其他文献

Constraint-based type-directed program synthesis

Peter-Michael Osera的其他文献

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{{ truncateString('Peter-Michael Osera', 18)}}的其他基金

EAGER: Semi-automated Type-directed Programming
EAGER:半自动类型定向编程
  • 批准号:
    1651817
  • 财政年份:
    2016
  • 资助金额:
    $ 52.46万
  • 项目类别:
    Standard Grant

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