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，每个项目都有成千上万的项目，是Alexandria的新图书馆。它们包含有关软件和软件项目的大量软件和信息。科学家和工程师都有兴趣分析这些丰富的信息以检验重要的研究假设。但是，目前的进入障碍是令人难以置信的，因为需要深厚的专业知识和复杂的工具来编写程序来访问版本控制系统，存储和检索可行的数据子集，并执行所需的超大规模分析。目标是加快软件工程研究的速度，并提高可重复性和可复制性，同时正确地策划数据和分析。该项目正在建立一个名为BOA的CISE研究基础设施，以帮助和协助此类研究，并将在全球范围内提供。该项目设计了一种新的编程语言，可以隐藏通过编程性访问版本控制系统，数据存储和检索，数据挖掘以及来自科学家和工程师并行化的详细信息，并允许他们专注于程序逻辑。该项目还设计了BOA的数据挖掘基础架构，以及一个包含700,000多个开源项目的BigData存储库，用于分析超大规模的软件存储库，以帮助进行此类实验。 BOA的更广泛影响源于其潜力使开发人员，设计师和研究人员能够建立直觉，多模式，以用户为中心的科学应用，这些应用程序可以帮助和实现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。这一进步将主要通过显着降低进入障碍，从而实现这一领域的更大，更雄心勃勃的数据密集型科学发现线。