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CAREER: Data-Driven Debugging of Complex Program Changes

CAREER: Data-Driven Debugging of Complex Program Changes
职业:复杂程序更改的数据驱动调试
批准号:
1845446
负责人:
Na Meng
金额:
$50.0万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-05-01 至 2024-04-30

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中文摘要
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英文摘要
After the initial release of a software application, developers continue changing it by adding new features, fixing software defects, or improving the implementation of existing features. As the application becomes older and larger, program changes become more complex. It becomes more difficult for developers to change or maintain the software efficiently and correctly. Slowly and incorrectly evolved software systems negatively impact both software producers and consumers; these systems can cause tremendous economic costs, put customers' data and privacy at risk, and even threaten people's lives. This project addresses this problem by helping computers and developers better understand, check, and apply complex changes. The project's novelty is in new methods and tools to characterize, model, validate, and suggest code modifications. The project's impacts are increasing programmer productivity, improving software reliability, reducing software cost, and protecting people and privacy data from issues caused by problematic software upgrades. The project will conduct empirical studies of software projects (in the GitHub repository) to understand and characterize multi-change edits "in the wild" to discover frequently co-changed patterns among code and non-code entities. Using these inferred patterns, the project will classify multi-change edits into different types such as bug fixes, refactorings, and feature enhancements. Techniques will be devised to make multi-edit changes, to ensure their correctness, and to automatically repair programs' multi-change edit sequences. These capabilities will be combined with delta debugging and dynamic patch validation in a a prototype editing and testing tool called Oedit, which will automatically recover programs from erroneous software updates and upgrades. The long-term vision is to provide a programming environment that supports complex, multi-change edits, with attention to their correctness, and with self-healing capabilities.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.
期刊论文(16)
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科研奖励(0)
会议论文
DOI: 10.1109/icsme46990.2020.00071
发表时间: 2020-05
期刊: 2020 IEEE International Conference on Software Maintenance and Evolution (ICSME)
影响因子: --
作者: [Pronnoy Goswami;Saksham Gupta;Zhiyuan Li;Na Meng;Daphne Yao]
通讯作者: Pronnoy Goswami;Saksham Gupta;Zhiyuan Li;Na Meng;Daphne Yao
DOI: 10.1145/3377811.3380922
发表时间: 2020-06
期刊: 2020 IEEE/ACM 42nd International Conference on Software Engineering (ICSE)
影响因子: --
作者: [Hao Zhong;Na Meng;Zexuan Li;Li Jia]
通讯作者: Hao Zhong;Na Meng;Zexuan Li;Li Jia
DOI: 10.1145/3524610.3527895
发表时间: 2022-03
期刊: 2022 IEEE/ACM 30th International Conference on Program Comprehension (ICPC)
影响因子: --
作者: [Y. Zhang;Ya Xiao;Md Mahir Asef Kabir;D. Yao;Na Meng]
通讯作者: Y. Zhang;Ya Xiao;Md Mahir Asef Kabir;D. Yao;Na Meng
DOI: 10.1145/3551349.3556950
发表时间: 2022-10
期刊: Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering
影响因子: --
作者: [Sheikh Shadab Towqir;Bowen Shen;Muhammad Ali Gulzar;Na Meng]
通讯作者: Sheikh Shadab Towqir;Bowen Shen;Muhammad Ali Gulzar;Na Meng
14
    Collaborative Research: SHF: Small: Reuse and Migration of GUI Tests
    CRII: SHF: Analysis and Automation of Global Systematic Changes
    国内基金
    海外基金
    Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
    Data-driven Recommendation System Construction of an Online Medical Platform Based on the Fusion of Information
    Development of a Linear Stochastic Model for Wind Field Reconstruction from Limited Measurement Data
    • 批准号:
      --
    • 项目类别:
      --
    • 资助金额:
      40万元
    • 批准年份:
      2020
    • 负责人:
      Vikrant Gupta
    • 依托单位:
    基于Linked Open Data的Web服务语义互操作关键技术
    • 批准号:
      61373035
    • 项目类别:
      面上项目
    • 资助金额:
      77.0万元
    • 批准年份:
      2013
    • 负责人:
      冯志勇
    • 依托单位: