CAREER: Robustness Analysis of Uncertain Programs: Theory, Algorithms, and Tools

职业:不确定程序的鲁棒性分析:理论、算法和工具

基本信息

  • 批准号:
    1156059
  • 负责人:
  • 金额:
    $ 34.54万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2011
  • 资助国家:
    美国
  • 起止时间:
    2011-07-01 至 2017-04-30
  • 项目状态:
    已结题

项目摘要

This research program will develop mathematical techniques to automatically prove the robustness of computer programs operating under uncertainty. The aim is to bridge the gap between control-theoretic studies of robustness, on the one hand, and program semantics and analysis on the other. In cyberphysical systems, where sensor-derived data from the physical world is intertwined with computations, uncertainty arises from volatile or erroneous sensor data. Such systems demand predictable responses to perturbations of the system's initial conditions, otherwise they will be unreliable. The project has three themes: (1) Theory: It will create comprehensive semantics of robustness properties such as continuity and stability in the setting of imperative programs over complex data types. (2) Algorithms: Analysis algorithms are needed to prove robustness of programs, or alternately find violations of robustness. Scalable, lightweight analyses will be developed along with precise but heavyweight methods. (3) Tools: These analyses will be implemented in tools applicable to software for real-world cyber-physical systems.
这项研究计划将开发数学技术,以自动证明计算机程序在不确定条件下运行的健壮性。其目的是弥合健壮性控制理论研究与程序语义和分析之间的差距。在信息物理系统中,传感器从物理世界获得的数据与计算交织在一起,不确定性来自不稳定的或错误的传感器数据。这样的系统需要对系统初始条件的扰动做出可预测的响应,否则它们将是不可靠的。该项目有三个主题:(1)理论:它将创建复杂数据类型上命令式程序设置中的健壮性属性的全面语义,如连续性和稳定性。(2)算法:需要分析算法来证明程序的健壮性,或者交替发现违反健壮性的行为。可扩展的轻量级分析将与精确但重量级的方法一起开发。(3)工具:这些分析将在适用于现实世界网络物理系统软件的工具中实施。

项目成果

期刊论文数量(0)
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专利数量(0)

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Swarat Chaudhuri其他文献

L G ] 1 0 A pr 2 01 9 Programmatically Interpretable Reinforcement Learning
LG ] 1 0 A pr 2 01 9 程序化可解释的强化学习
  • DOI:
  • 发表时间:
    2019
  • 期刊:
  • 影响因子:
    0
  • 作者:
    A. Verma;VijayaraghavanMurali;Rishabh Singh;Pushmeet Kohli;Swarat Chaudhuri
  • 通讯作者:
    Swarat Chaudhuri
Data-Driven Program Completion
数据驱动的程序完成
  • DOI:
  • 发表时间:
    2017
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Yanxin Lu;Swarat Chaudhuri;C. Jermaine;David Melski
  • 通讯作者:
    David Melski
On-the-Fly Reachability and Cycle Detection for Recursive State Machines
递归状态机的动态可达性和循环检测
  • DOI:
    10.1007/978-3-540-31980-1_5
  • 发表时间:
    2005
  • 期刊:
  • 影响因子:
    0
  • 作者:
    R. Alur;Swarat Chaudhuri;K. Etessami;P. Madhusudan
  • 通讯作者:
    P. Madhusudan
A fixpoint calculus for local and global program flows
局部和全局程序流的不动点演算
Controller synthesis with inductive proofs for piecewise linear systems: An SMT-based algorithm
分段线性系统的控制器综合与归纳证明:基于 SMT 的算法

Swarat Chaudhuri的其他文献

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{{ truncateString('Swarat Chaudhuri', 18)}}的其他基金

SHF: Medium: Neurosymbolic Agents for Formal Theorem-Proving
SHF:介质:用于形式定理证明的神经符号代理
  • 批准号:
    2403211
  • 财政年份:
    2024
  • 资助金额:
    $ 34.54万
  • 项目类别:
    Continuing Grant
Collaborative Research: PPoSS: Large: A Full-stack Approach to Declarative Analytics at Scale
协作研究:PPoSS:大型:大规模声明性分析的全栈方法
  • 批准号:
    2316161
  • 财政年份:
    2023
  • 资助金额:
    $ 34.54万
  • 项目类别:
    Continuing Grant
Collaborative Research: SHF: Medium: Semantics-Aware Neural Models of Code
合作研究:SHF:媒介:代码的语义感知神经模型
  • 批准号:
    2212559
  • 财政年份:
    2022
  • 资助金额:
    $ 34.54万
  • 项目类别:
    Standard Grant
SHF: Medium: Collaborative Research: Bridging Automated Formal Reasoning and Continuous Optimization for Provably Safe Deep Learning
SHF:中:协作研究:连接自动形式推理和持续优化以实现可证明安全的深度学习
  • 批准号:
    2033851
  • 财政年份:
    2020
  • 资助金额:
    $ 34.54万
  • 项目类别:
    Standard Grant
SHF: Medium: Collaborative Research: Bridging Automated Formal Reasoning and Continuous Optimization for Provably Safe Deep Learning
SHF:中:协作研究:连接自动形式推理和持续优化以实现可证明安全的深度学习
  • 批准号:
    1901284
  • 财政年份:
    2019
  • 资助金额:
    $ 34.54万
  • 项目类别:
    Standard Grant
SHF: Small: Computer-Aided Grading, Feedback, and Assignment Creating in Massive Online Programming Courses
SHF:小型:大规模在线编程课程中的计算机辅助评分、反馈和作业创建
  • 批准号:
    1320860
  • 财政年份:
    2013
  • 资助金额:
    $ 34.54万
  • 项目类别:
    Standard Grant
SHF: Medium: Collaborative Research: Marrying Program Analysis and Numerical Search
SHF:媒介:协作研究:程序分析与数值搜索的结合
  • 批准号:
    1162076
  • 财政年份:
    2012
  • 资助金额:
    $ 34.54万
  • 项目类别:
    Continuing Grant
SHF: Medium: Collaborative Research: Chorus: Dynamic Isolation in Shared-Memory Parallelism
SHF:媒介:协作研究:Chorus:共享内存并行中的动态隔离
  • 批准号:
    1242507
  • 财政年份:
    2011
  • 资助金额:
    $ 34.54万
  • 项目类别:
    Continuing Grant
CAREER: Robustness Analysis of Uncertain Programs: Theory, Algorithms, and Tools
职业:不确定程序的鲁棒性分析:理论、算法和工具
  • 批准号:
    0953507
  • 财政年份:
    2010
  • 资助金额:
    $ 34.54万
  • 项目类别:
    Continuing Grant
SHF: Medium: Collaborative Research: Chorus: Dynamic Isolation in Shared-Memory Parallelism
SHF:媒介:协作研究:Chorus:共享内存并行中的动态隔离
  • 批准号:
    0964443
  • 财政年份:
    2010
  • 资助金额:
    $ 34.54万
  • 项目类别:
    Continuing Grant

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Parallelization and robustness of random walks: Approaches from "short" random walks analysis
随机游走的并行化和鲁棒性:“短”随机游走分析的方法
  • 批准号:
    23K16840
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