SHF: Medium: Collaborative Research: Enhancing Continuous Integration Testing for the Open-Source Ecosystem

SHF:媒介:协作研究:加强开源生态系统的持续集成测试

基本信息

  • 批准号:
    1763788
  • 负责人:
  • 金额:
    $ 43.71万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2018
  • 资助国家:
    美国
  • 起止时间:
    2018-10-01 至 2024-09-30
  • 项目状态:
    已结题

项目摘要

Continuous integration (CI) is an important software development activity that aims to improve software development by automating software compilation and regression testing. Recent studies report that CI helps developers deploy faster and reduce development cost. Given these success stories, CI has attracted rapidly increasing interest and adoption, e.g., Travis CI, the currently most popular CI service, is used by over 300,000 GitHub projects. Despite the success of CI, developers report they would like to see improvements in CI. First, they want to faster obtain regression test results. Second, they want better handling of so-called flaky tests, which are regression tests that can non-deterministically pass or fail, and whose failures negatively affect developer's productivity. Third, developers report that CI builds do not provide sufficient debugging assistance for reasoning about failed regression tests. While regression testing has been studied for over three decades, it has not been studied in the context of CI until recently.To substantially improve regression testing in CI, the PIs propose to develop novel techniques and tools that address three important challenges: (1) test selection to speed up regression testing and the development cycle, (2) test reliability to mitigate the problems that flaky tests introduce, and (3) debugging assistance to ease the effort of diagnosing and fixing the true and flaky regression test failures. The PIs plan to develop techniques and tools based on a mix of static and dynamic program analyses, leveraging not only information from two project revisions (as traditional in regression testing) but also from all historical build and testing information available in CI testing. The PIs plan to embody their techniques in a tool-set and evaluate them extensively on open-source projects and in industrial collaborations. The broader impacts of enhancing continuous integration testing are to allow software developers to faster build higher quality software, which can benefit our modern society that greatly depends on software.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.
持续集成(CI)是一项重要的软件开发活动,旨在通过自动化软件编译和回归测试来改进软件开发。最近的研究报告称,CI帮助开发人员更快地部署并降低开发成本。鉴于这些成功的案例,CI吸引了越来越多的人的兴趣和采用,例如,目前最受欢迎的CI服务Travis CI被30多万个GitHub项目使用。尽管CI取得了成功,但开发人员报告说,他们希望看到CI的改进。首先,他们希望更快地获得回归测试结果。其次,他们希望更好地处理所谓的薄片测试,这是一种回归测试,可以不确定地通过或失败,其失败会对开发人员的生产力产生负面影响。第三,开发人员报告说,CI构建不能为失败的回归测试提供足够的调试帮助。回归测试已经被研究了三十多年,但直到最近才在CI的背景下进行研究。为了显著改善CI中的回归测试,PI建议开发新的技术和工具来解决三个重要挑战:(1)测试选择以加快回归测试和开发周期;(2)测试可靠性以缓解片状测试带来的问题;(3)调试辅助以简化诊断和修复真实和片状回归测试失败的工作。PI计划开发基于静态和动态程序分析的技术和工具,不仅利用来自两个项目修订版的信息(回归测试中的传统),而且利用CI测试中可用的所有历史构建和测试信息。私人投资机构计划将他们的技术体现在一个工具集中,并在开源项目和工业合作中对其进行广泛的评估。加强持续集成测试的更广泛影响是允许软件开发人员更快地构建更高质量的软件,这可以使我们严重依赖软件的现代社会受益。该奖项反映了NSF的法定使命,并通过使用基金会的智力优势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(18)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
A large-scale longitudinal study of flaky tests
  • DOI:
    10.1145/3428270
  • 发表时间:
    2020-11
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Wing Lam;Stefan Winter;Anjiang Wei;Tao Xie;D. Marinov;Jonathan Bell
  • 通讯作者:
    Wing Lam;Stefan Winter;Anjiang Wei;Tao Xie;D. Marinov;Jonathan Bell
Techniques for Evolution-Aware Runtime Verification
iFixFlakies: a framework for automatically fixing order-dependent flaky tests
Initial Results on Counting Test Orders for Order-Dependent Flaky Tests Using Alloy
  • DOI:
    10.1007/978-3-031-04673-5_9
  • 发表时间:
    2021
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Wenxi Wang;Pu Yi;S. Khurshid;D. Marinov
  • 通讯作者:
    Wenxi Wang;Pu Yi;S. Khurshid;D. Marinov
Automatic Reproduction of Workflows in the Snakemake Workflow Catalog and nf-core Registries
自动复制 Snakemake 工作流程目录和 nf-core 注册表中的工作流程
{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

Darko Marinov其他文献

Reproducing and Improving the BugsInPy Dataset
重现和改进 BugsInPy 数据集
TestEra: Specification-Based Testing of Java Programs Using SAT
  • DOI:
    10.1023/b:ause.0000038938.10589.b9
  • 发表时间:
    2004-10-01
  • 期刊:
  • 影响因子:
    3.100
  • 作者:
    Sarfraz Khurshid;Darko Marinov
  • 通讯作者:
    Darko Marinov
FastFlip: Compositional Error Injection Analysis
FastFlip:组合错误注入分析
  • DOI:
    10.48550/arxiv.2403.13989
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Keyur Joshi;Rahul Singh;Tommaso Bassetto;Sarita Adve;Darko Marinov;Sasa Misailovic
  • 通讯作者:
    Sasa Misailovic

Darko Marinov的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('Darko Marinov', 18)}}的其他基金

EAGER: USBRCCR: Collaborative: Lightweight Policy Enforcement of Information Flows in IoT Infrastructures
EAGER:USBRCCR:协作:物联网基础设施中信息流的轻量级策略执行
  • 批准号:
    1740916
  • 财政年份:
    2017
  • 资助金额:
    $ 43.71万
  • 项目类别:
    Standard Grant
CPS: Synergy: Collaborative Research: Support for Security and Safety of Programmable IoT Systems
CPS:协同:协作研究:支持可编程物联网系统的安全性
  • 批准号:
    1646305
  • 财政年份:
    2017
  • 资助金额:
    $ 43.71万
  • 项目类别:
    Standard Grant
SHF: Medium: Collaborative Research: Improved Performance Testing and Debugging
SHF:中:协作研究:改进的性能测试和调试
  • 批准号:
    1409423
  • 财政年份:
    2014
  • 资助金额:
    $ 43.71万
  • 项目类别:
    Standard Grant
SHF: Small: Revisiting Assumptions of Regression Testing
SHF:小:重新审视回归测试的假设
  • 批准号:
    1421503
  • 财政年份:
    2014
  • 资助金额:
    $ 43.71万
  • 项目类别:
    Standard Grant
Collaborative Research: II-EN: Infrastructure Support for Software Testing Research
协作研究:II-EN:软件测试研究的基础设施支持
  • 批准号:
    0958199
  • 财政年份:
    2010
  • 资助金额:
    $ 43.71万
  • 项目类别:
    Continuing Grant
SHF: Small: IMUnit: Improved Multithreaded Unit Testing
SHF:小:IMUnit:改进的多线程单元测试
  • 批准号:
    0916893
  • 财政年份:
    2009
  • 资助金额:
    $ 43.71万
  • 项目类别:
    Standard Grant
CAREER: Systematic Software Testing Using Test Abstractions
职业:使用测试抽象进行系统软件测试
  • 批准号:
    0746856
  • 财政年份:
    2008
  • 资助金额:
    $ 43.71万
  • 项目类别:
    Continuing Grant

相似海外基金

Collaborative Research: SHF: Medium: Differentiable Hardware Synthesis
合作研究:SHF:媒介:可微分硬件合成
  • 批准号:
    2403134
  • 财政年份:
    2024
  • 资助金额:
    $ 43.71万
  • 项目类别:
    Standard Grant
Collaborative Research: SHF: Medium: Enabling Graphics Processing Unit Performance Simulation for Large-Scale Workloads with Lightweight Simulation Methods
合作研究:SHF:中:通过轻量级仿真方法实现大规模工作负载的图形处理单元性能仿真
  • 批准号:
    2402804
  • 财政年份:
    2024
  • 资助金额:
    $ 43.71万
  • 项目类别:
    Standard Grant
Collaborative Research: SHF: Medium: Tiny Chiplets for Big AI: A Reconfigurable-On-Package System
合作研究:SHF:中:用于大人工智能的微型芯片:可重新配置的封装系统
  • 批准号:
    2403408
  • 财政年份:
    2024
  • 资助金额:
    $ 43.71万
  • 项目类别:
    Standard Grant
Collaborative Research: SHF: Medium: Toward Understandability and Interpretability for Neural Language Models of Source Code
合作研究:SHF:媒介:实现源代码神经语言模型的可理解性和可解释性
  • 批准号:
    2423813
  • 财政年份:
    2024
  • 资助金额:
    $ 43.71万
  • 项目类别:
    Standard Grant
Collaborative Research: SHF: Medium: Enabling GPU Performance Simulation for Large-Scale Workloads with Lightweight Simulation Methods
合作研究:SHF:中:通过轻量级仿真方法实现大规模工作负载的 GPU 性能仿真
  • 批准号:
    2402806
  • 财政年份:
    2024
  • 资助金额:
    $ 43.71万
  • 项目类别:
    Standard Grant
Collaborative Research: SHF: Medium: Differentiable Hardware Synthesis
合作研究:SHF:媒介:可微分硬件合成
  • 批准号:
    2403135
  • 财政年份:
    2024
  • 资助金额:
    $ 43.71万
  • 项目类别:
    Standard Grant
Collaborative Research: SHF: Medium: Tiny Chiplets for Big AI: A Reconfigurable-On-Package System
合作研究:SHF:中:用于大人工智能的微型芯片:可重新配置的封装系统
  • 批准号:
    2403409
  • 财政年份:
    2024
  • 资助金额:
    $ 43.71万
  • 项目类别:
    Standard Grant
Collaborative Research: SHF: Medium: Enabling GPU Performance Simulation for Large-Scale Workloads with Lightweight Simulation Methods
合作研究:SHF:中:通过轻量级仿真方法实现大规模工作负载的 GPU 性能仿真
  • 批准号:
    2402805
  • 财政年份:
    2024
  • 资助金额:
    $ 43.71万
  • 项目类别:
    Standard Grant
Collaborative Research: SHF: Medium: High-Performance, Verified Accelerator Programming
合作研究:SHF:中:高性能、经过验证的加速器编程
  • 批准号:
    2313024
  • 财政年份:
    2023
  • 资助金额:
    $ 43.71万
  • 项目类别:
    Standard Grant
Collaborative Research: SHF: Medium: Verifying Deep Neural Networks with Spintronic Probabilistic Computers
合作研究:SHF:中:使用自旋电子概率计算机验证深度神经网络
  • 批准号:
    2311295
  • 财政年份:
    2023
  • 资助金额:
    $ 43.71万
  • 项目类别:
    Continuing Grant
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了