Software Processes for Small Teams Developing Scalable Applications in the Cloud

小型团队在云中开发可扩展应用程序的软件流程

• 批准号: 203166-2013
• 负责人: Maurer, Frank
• 金额: $ 1.82万
• 依托单位: University of Calgary
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=569885
• 关键词: Software; Processes; Small; Teams; Developing

In the future, more and more software systems are expected to utilize cloud-based infrastructure to address the "big data" challenge. "Big data" applications pose severe software engineering challenges, including: - What design strategies will better accommodate rapid increases in the data size and the number of users? - How can we effectively test scalable service-based cloud applications? - How can we design software applications that rely on external services so that they are easy to evolve? And how can we design software in a way that allows migration of components among different cloud providers? Small teams, as typically found in small & medium sized enterprises (SME), are particularly challenged in developing "big data" applications due to resource constraints imposed from limited budgets. To build on my group's results and research strengths, our research will look at these issues from a software development perspective. Concretely, we will focus on: - Scalable Software-as-a-Service (SaaS) applications: We will work closely with partners to conduct case studies of how cloud-based applications are developed. We plan to investigate software engineering practices that small teams can use to build scalable "big data" applications for the Cloud. - Test-driven development: We will investigate test-driven development for building "big data" software applications in the cloud. We intend to develop rule-bases for common defects of cloud-based applications. - Software design & API usability: We will study design patterns and develop guidelines enabling small teams to design, scale, and evolve cloud-based applications. We also intend to study and evaluate the usability and portability of software APIs for building cloud-based applications.

未来，预计将有越来越多的软件系统利用基于云的基础设施来应对“大数据”挑战。“大数据”应用程序带来了严峻的软件工程挑战，包括： -哪些设计策略将更好地适应数据大小和用户数量的快速增长？ -我们如何有效地测试可扩展的基于服务的云应用？ -我们如何设计依赖于外部服务的软件应用程序，使其易于发展？我们如何才能设计出一种允许组件在不同云提供商之间迁移的软件？ 由于有限预算的资源限制，中小型企业(SME)中的小型团队在开发“大数据”应用程序方面面临着特别大的挑战。 为了在我的团队的结果和研究优势的基础上，我们的研究将从软件开发的角度来看待这些问题。具体地说，我们将重点关注： -可扩展的软件即服务(SaaS)应用：我们将与合作伙伴密切合作，就如何开发基于云的应用进行案例研究。我们计划调查软件工程实践，小型团队可以使用这些实践为云构建可伸缩的“大数据”应用程序。 -测试驱动开发：我们将研究测试驱动开发在云上构建大数据软件应用。我们打算为基于云的应用程序的常见缺陷开发规则库。 -软件设计和API可用性：我们将研究设计模式并制定指导方针，使小型团队能够设计、扩展和发展基于云的应用程序。我们还打算研究和评估用于构建基于云的应用程序的软件API的可用性和可移植性。