CI-EN: Boa: Enhancing Infrastructure for Studying Software and its Evolution at a Large Scale

CI-EN：Boa：增强大规模研究软件及其演化的基础设施

基本信息

批准号：
1513263
负责人：
Hridesh Rajan
金额：
$ 142.69万
依托单位：
Iowa State University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2015
资助国家：
美国
起止时间：
2015-06-01 至 2021-05-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1513263&HistoricalAwards=false
关键词：
CI EN Boa Enhancing Infrastructure

项目摘要

In today's software-centric world, ultra-large-scale software repositories, e.g., SourceForge, GitHub, and Google Code, with hundreds of thousands of projects each, are the new library of Alexandria. They contain an enormous corpus of software and information about software and software projects. Scientists and engineers alike are interested in analyzing this wealth of information to test important research hypotheses. However, the current barrier to entry is prohibitive because deep expertise and sophisticated tools are needed to write programs that access version control systems, store and retrieve workable data subsets, and perform the needed ultra-large-scale analysis. The goal is accelerate the pace of Software Engineering research and to increase reusability and replicability, while properly curating the data and analyses. This project is building a CISE research infrastructure called Boa to aid and assist with such research and will be globally available. The project designs a new programming language 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 also designs a data mining infrastructure for Boa, and a BIGDATA repository containing 700,000+ open source projects for analyzing ultra-large-scale software repositories to help with such experiments. The broader impacts of Boa 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.

在当今以软件为中心的世界中，超大规模的软件存储库，例如 SourceForge、GitHub 和 Google Code，每个存储库都有数十万个项目，是亚历山大的新图书馆。它们包含大量软件以及有关软件和软件项目的信息。科学家和工程师都对分析这些丰富的信息来测试重要的研究假设感兴趣。然而，当前的进入壁垒令人望而却步，因为需要深厚的专业知识和复杂的工具来编写访问版本控制系统、存储和检索可用数据子集以及执行所需的超大规模分析的程序。目标是加快软件工程研究的步伐，提高可重用性和可复制性，同时正确管理数据和分析。该项目正在建设一个名为 Boa 的 CISE 研究基础设施，以协助和协助此类研究，并将在全球范围内使用。该项目设计了一种新的编程语言，可以向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。该项目还为 Boa 设计了数据挖掘基础设施，以及包含 700,000 多个开源项目的 BIGDATA 存储库，用于分析超大规模软件存储库，以帮助进行此类实验。 Boa 的更广泛影响源于其使开发人员、设计人员和研究人员能够构建直观、多模式、以用户为中心的科学应用程序的潜力，这些应用程序可以帮助和实现对个人、社会、法律、政策和技术方面的科学研究。开源软件开发。这一进步主要通过显着降低进入门槛来实现，从而在该领域实现更大规模、更雄心勃勃的数据密集型科学发现。