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DASS: Enabling Comprehensive and Interactive Open Source Software License Compliance

DASS: Enabling Comprehensive and Interactive Open Source Software License Compliance
DASS:实现全面、交互式的开源软件许可证合规性
批准号:
2217733
负责人:
Denys Poshyvanyk
金额:
$75.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2022
资助国家:
美国
项目状态:
未结题
起止时间:
2022-10-01 至 2025-09-30

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中文摘要
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英文摘要
Because software is protected under U.S. copyright law, software licenses represent an important legal consideration in software engineering. A license defines the terms pursuant to which software can legally be distributed, modified, and (re)used. While certain software licenses, known as open-source licenses, allow considerable use of the software in future projects by other engineers, such licenses still come with conditions that must be complied with in order to use the software legally. Determining the nature and extent of those conditions can be challenging for software engineers, who are typically not trained in the intricacies of the law. Reusing, adapting, or distributing software without abiding by its license terms can lead to significant legal and economic consequences. Software engineers need a better understanding of the licensing issues that they face and their implications, as well as guidance to address these issues, and legal practitioners need better support in collecting the information necessary for assessing licensing-related legal issues. To address these fundamental challenges, this project will conduct a series of user studies with software engineers and legal professionals to understand their needs and preferences in solving issues related to software licensing. Based on the acquired knowledge from the studies, this project will aim to develop a conversational system that will allow software engineers to address their licensing needs and issues interactively, and more efficiently and effectively, compared to existing solutions, thus preventing software license incompatibilities. The proposed system will also assist legal professionals in collecting the technical and legal information they require for solving software licensing cases. The project will produce and disseminate educational materials on the acquired knowledge in order to further the provision of legal information and guidance through interactive/conversational solutions. These materials are intended to be integrated into computing and law curricula. In addition, the project will focus on recruiting and retaining computer science and law students from traditionally underrepresented categories. The project is centered on five specific goals. First, it will create comprehensive taxonomies of licensing needs, issues, exceptions, and misconceptions for software engineers. Second, it will determine the primary legal questions that need to be answered in determining license compatibility and the information required to answer those questions. Third, it will build a comprehensive database of existing open-source licenses that encodes licensing terms and their relationships, including exceptions and other conditions, and language incompatibilities across distinct licenses. Fourth, it will elicit design requirements and user preferences for interactive license compliance. Finally, it will design, develop, and evaluate an interactive solution that uses collected data to engage with engineers and provide guidance on license compliance in a way that will make future engagement with legal counsel more efficient and effective. This project aims to improve software accountability with respect to intellectual property law and open source licensing, by assisting developers and lawyers in understanding and addressing the licensing issues that arise in their work, and to contribute to the developing research on the automation and accessibility of legal services.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.
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Collaborative Research: SHF: Medium: Toward Understandability and Interpretability for Neural Language Models of Source Code
  • 批准号:
    2311469
  • 项目类别:
    Standard Grant
  • 资助金额:
    $32.92万
  • 财政年份:
    2023
  • 负责人:
    Denys Poshyvanyk
  • 依托单位:
SHF: Small: Towards a Holistic Causal Model for Continuous Software Traceability
  • 批准号:
    2007246
  • 项目类别:
    Standard Grant
  • 资助金额:
    $50.0万
  • 财政年份:
    2020
  • 负责人:
    Denys Poshyvanyk
  • 依托单位:
Collaborative Research: SHF: Medium: Bug Report Management 2.0
  • 批准号:
    1955853
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $79.13万
  • 财政年份:
    2020
  • 负责人:
    Denys Poshyvanyk
  • 依托单位:
EAGER: Mapping Future Synergies between Deep Learning and Software Engineering
  • 批准号:
    1927679
  • 项目类别:
    Standard Grant
  • 资助金额:
    $8.28万
  • 财政年份:
    2019
  • 负责人:
    Denys Poshyvanyk
  • 依托单位:
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