Collaborative Research: CCRI: ENS: Boa 2.0: Enhancing Infrastructure for Studying Software and its Evolution at a Large Scale

在当今以软件为中心的世界里，超大规模的软件存储库，例如GitHub，每个库都有数十万个项目，是新的亚历山大图书馆。它们包含了大量的软件和关于软件的信息。科学家和工程师都对分析这些丰富的信息感兴趣，既是出于好奇，也是为了检验重要的研究假设。然而，目前的进入门槛令人望而却步，只有少数拥有完善的基础设施和深厚的专业知识的人可以尝试这种超大规模的分析。必要的专业知识包括：以编程方式访问版本控制系统、数据存储和检索、数据挖掘和并行化。对这四个不同领域的专业知识的需求显著地增加了试图回答涉及超大规模软件存储库的研究问题的科学研究的成本。因此，实验通常是不可复制的，并且实验基础设施的可重用性很低。此外，由于没有系统的管理，与此类实验相关和产生的数据经常丢失，变得难以获取和过时。最后但并非最不重要的一点是，构建分析基础设施以有效地处理超大规模数据可能非常困难。该项目将继续加强CISE研究基础设施，称为Boa，以帮助和协助此类研究。下一个版本的Boa将被称为Boa 2.0，并将继续在全球传播。该项目将进一步开发称为Boa的编程语言，该语言可以对科学家和工程师隐藏以编程方式访问版本控制系统、数据存储和检索、数据挖掘和并行化的细节，使他们能够专注于程序逻辑。该项目还将增强Boa的数据挖掘基础设施，以及一个包含数百万个开源项目的BIGDATA存储库，用于分析超大型软件存储库，以帮助进行此类实验。该项目将把Boa 2.0与开放科学开放科学框架中心（OSF）集成，以提高可重复性，并与国家计算资源XSEDE集成，以提高可扩展性。Boa 2.0的广泛影响源于它的潜力，它使开发人员、设计人员和研究人员能够构建直观的、多模式的、以用户为中心的科学应用程序，这些应用程序可以帮助并实现对开源软件开发的个人、社会、法律、政策和技术方面的科学研究。这一进展将主要通过大幅降低进入门槛来实现，从而在该领域实现更大、更雄心勃勃的数据密集型科学发现。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

In today’s software-centric world, ultra-large-scale software repositories, e.g. GitHub, with hundreds of thousands of projects each, are the new library of Alexandria. They contain an enormous corpus of software and information about software. Scientists and engineers alike are interested in analyzing this wealth of information both for curiosity as well as for testing important research hypotheses. However, the current barrier to entry is prohibitive and only a few with well-established infrastructure and deep expertise can attempt such ultra-large-scale analysis. Necessary expertise includes: programmatically accessing version control systems, data storage and retrieval, data mining, and parallelization. The need to have expertise in these four different areas significantly increases the cost of scientific research that attempts to answer research questions involving ultra-large-scale software repositories. As a result, experiments are often not replicable, and reusability of experimental infrastructure low. Furthermore, data associated and produced by such experiments is often lost and becomes inaccessible and obsolete, because there is no systematic curation. Last but not least, building analysis infrastructure to process ultra-large-scale data efficiently can be very hard. This project will continue to enhance the CISE research infrastructure called Boa to aid and assist with such research. This next version of Boa will be called Boa 2.0 and it will continue to be globally disseminated. The project will further develop the programming language also called Boa, that can hide the details of programmatically accessing version control systems, data storage and retrieval, data mining, and parallelization from the scientists and engineers and allow them to focus on the program logic. The project will also enhance the data mining infrastructure for Boa, and a BIGDATA repository containing millions of open source project for analyzing ultra-large-scale software repositories to help with such experiments. The project will integrate Boa 2.0 with the Center for Open Science Open Science Framework (OSF) to improve reproducibility and with the national computing resource XSEDE to improve scalability. The broader impacts of Boa 2.0 stem from its potential to enable developers, designers and researchers to build intuitive, multi-modal, user-centric, scientific applications that can aid and enable scientific research on individual, social, legal, policy, and technical aspects of open source software development. This advance will primarily be achieved by significantly lowering the barrier to entry and thus enabling a larger and more ambitious line of data-intensive scientific discovery in this area.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.