CAREER: Data-Driven Debugging of Complex Program Changes
CAREER: Data-Driven Debugging of Complex Program Changes
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
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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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
DOI:
10.1145/3324884.3416577
发表时间:
2020-09
期刊:
2020 35th IEEE/ACM International Conference on Automated Software Engineering (ASE)
影响因子:
--
作者:
[Chengyuan Wen;Yaxuan Zhang;Xiao He;Na Meng]
通讯作者:
Chengyuan Wen;Yaxuan Zhang;Xiao He;Na Meng
共 14 条
Collaborative Research: SHF: Small: Reuse and Migration of GUI Tests
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批准号:2006278
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项目类别:Standard Grant
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资助金额:$25.0万
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财政年份:2020
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负责人:Na Meng
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依托单位:
CRII: SHF: Analysis and Automation of Global Systematic Changes
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批准号:1565827
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项目类别:Standard Grant
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资助金额:$17.5万
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财政年份:2016
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负责人:Na Meng
-
依托单位:
国内基金
海外基金
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Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
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Data-driven Recommendation System Construction of an Online Medical Platform Based on the Fusion of Information
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项目类别:外国青年学者研究基金项目
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批准年份:2024
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负责人:江洋子
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Molecular Interaction Reconstruction of Rheumatoid Arthritis Therapies Using Clinical Data
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批准号:31070748
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负责人:Christine Nardini
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高维数据的函数型数据(functional data)分析方法
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负责人:周迎春
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染色体复制负调控因子datA在细胞周期中的作用
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批准号:31060015
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资助金额:25.0万元
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批准年份:2010
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负责人:莫日根
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Computational Methods for Analyzing Toponome Data
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负责人:Axel Mosig
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