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CAREER: Maximal and Scalable Unified Debugging for the JVM Ecosystem

CAREER: Maximal and Scalable Unified Debugging for the JVM Ecosystem
职业:JVM 生态系统的最大且可扩展的统一调试
批准号:
2131943
负责人:
Lingming Zhang
金额:
$51.98万
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
项目状态:
未结题
起止时间:
2021-07-15 至 2026-04-30

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中文摘要
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英文摘要
The software industry all over the world has contributed to the massive culture of support around Java, one of the most popular programming languages. The Java runtime, or Java Virtual Machine (JVM), has become a software ecosystem on its own. Nowadays, hundreds of popular JVM languages (including Kotlin, Scala, and Groovy) have been developed/adopted under different platforms (including Oracle JDK and Android SDK), build systems (including Gradle and Maven), and JVM implementations (including HotSpot and OpenJ9). For example, Google just promoted Kotlin to the No.1 preferred language for Android development at Google I/O 2019. The huge and heterogeneous ecosystem of JVM raises unique challenges to automated debugging, including both fault localization and repair. This project proposes to re-think the role of a foundational concept of program mutation, that is, systematic program transformation, in automated debugging. Program mutation has been widely adopted in traditional mutation testing and program repair, and the investigator conjectures, based on preliminary work, that it can be used to transform and advance the state-of-the-art in automated debugging for software written with technologies from the entire JVM ecosystem and beyond. Specifically, the project focuses on the following research thrusts: (1) unifying both fault localization and repair via program mutation to boost each other, (2) automatically inferring up-to-date advanced mutators from big code corpora for maximal unified debugging, since existing program mutators are often limited and may easily become obsolete, (3) developing novel techniques to optimize patch executions for scalable unified debugging, since patch execution can be extremely time-consuming, and (4) supporting unified debugging of the entire heterogeneous JVM ecosystem. The project will unify program mutations across various dimensions for the first time, e.g., across JVM languages and platforms, across code types (including source, test, and build code), and even across JVM boundaries. Ultimately, the project aims for a practical debugging system to benefit JVM ecosystem developers all over the world. The overarching idea of unified debugging can also substantially impact the ways that both researchers and practitioners view, design, and apply automated debugging -- fault localization always requires manual repair while program repair only works for some bugs; in contrast, unified debugging can support the most automated debugging possible for each bug, and broaden the effective range of the entire program repair area to all possible bugs. The project will integrate the research results into SE curriculum, K-12 camps, software testing contests, and industrial collaborations.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(19)
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会议论文
ITfuzz: Coverage-guided Fuzzing for JVM Just-in-Time Compilers
ITfuzz:针对 JVM 即时编译器的覆盖引导模糊测试
DOI: --
发表时间: 2023
期刊: Proceedings of the IEEE/ACM International Conference on Software Engineering
影响因子: --
作者: [Wu, Mingyuan, Lu, Minghai, Cui, Heming, Chen, Junjie, Zhang, Yuqun, Zhang, Lingming]
通讯作者: Zhang, Lingming
DOI: 10.1145/3510003.3510041
发表时间: 2022-01
期刊: 2022 IEEE/ACM 44th International Conference on Software Engineering (ICSE)
影响因子: --
作者: [Anjiang Wei;Yinlin Deng;Chenyuan Yang;Lingming Zhang]
通讯作者: Anjiang Wei;Yinlin Deng;Chenyuan Yang;Lingming Zhang
DOI: 10.1109/icse48619.2023.00154
发表时间: 2023-05
期刊: 2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE)
影响因子: --
作者: [Chun Xia;Saikat Dutta;D. Marinov]
通讯作者: Chun Xia;Saikat Dutta;D. Marinov
DOI: 10.1145/3510003.3510059
发表时间: 2022-05
期刊: 2022 IEEE/ACM 44th International Conference on Software Engineering (ICSE)
影响因子: --
作者: [Yingquan Zhao;Zan Wang;Junjie Chen;Mengdi Liu;Mingyuan Wu;Yuqun Zhang;Lingming Zhang]
通讯作者: Yingquan Zhao;Zan Wang;Junjie Chen;Mengdi Liu;Mingyuan Wu;Yuqun Zhang;Lingming Zhang
17
    SHF: Medium: Collaborative Research: Enhancing Continuous Integration Testing for the Open-Source Ecosystem
    CAREER: Maximal and Scalable Unified Debugging for the JVM Ecosystem
    • 批准号:
      1942430
    • 项目类别:
      Continuing Grant
    • 资助金额:
      $51.98万
    • 财政年份:
      2020
    • 负责人:
      Lingming Zhang
    • 依托单位:
    SHF: Medium: Collaborative Research: Enhancing Continuous Integration Testing for the Open-Source Ecosystem
    • 批准号:
      1763906
    • 项目类别:
      Continuing Grant
    • 资助金额:
      $36.3万
    • 财政年份:
      2018
    • 负责人:
      Lingming Zhang
    • 依托单位:
    CRII: SHF: Machine-Learning-Based Test Effectiveness Prediction
    • 批准号:
      1566589
    • 项目类别:
      Standard Grant
    • 资助金额:
      $17.42万
    • 财政年份:
      2016
    • 负责人:
      Lingming Zhang
    • 依托单位:
    海外基金