A Research Program in Requirements Engineering

需求工程研究项目

• 批准号: RGPIN-2018-06853
• 负责人: Madhavji, Nazim
• 金额: $ 2.48万
• 依托单位: University of Western Ontario
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=714502
• 关键词: Research; Program; Requirements; Engineering

The field of requirements engineering (RE) is one of the most strategic fields in the software engineering domain because it embodies methods, techniques, tools and processes for defining what the system should provide and how the system should behave during its use. There isn't any point in investing much effort in the rest of system development if there are major oversights in a system's requirements. While RE has made significant progress over the last several decades, there are evolving challenges in this field due to changing contexts, technologies, paradigms and the like; thus the quest for on-going improvements in the RE field. This proposal therefore seeks to address the following key challenges in the RE field: (i) Data intensive (or Big Data) end-user applications in different application-domains are steadily growing in number. Yet, in RE, current specification methods do not capture, explicitly, data characteristics of such systems. This is an inhibitor for efficiently creating dependable big data end-user applications. (ii) Ensuring system's compliance with regulations and standards, especially for large, complex, systems is hitherto arduous, effort-draining, and error prone, during the RE process. Current RE effort-estimation methods for compliance work are ad hoc and are not reliable. This leads to several problems, namely: resource allocation, product quality, reusability, and cycle-time. This research is important because effective specification methods and effort-estimation methods would reduce the described problems significantly. In turn, this will benefit the users and developers of big data and regulatory compliant systems. Researchers would also benefit because of the contributions to the body of knowledge in the RE field. The anticipated outcomes include novel methods for: specifying quality requirements for big data end-user systems, and estimating the effort needed to carry out regulatory compliance work in RE. With an increasing thrust for knowledge-based economy among Canadian corporations, the outcomes of the proposed research would help in promulgating this movement.

需求工程(RE)领域是软件工程领域中最具战略意义的领域之一，因为它体现了定义系统应该提供什么以及系统在使用期间应该如何行为的方法、技术、工具和过程。如果系统需求中存在重大疏忽，那么在系统开发的其余部分投入大量精力是没有任何意义的。虽然可再生能源在过去几十年中取得了重大进展，但由于不断变化的环境、技术、范例等，这一领域也面临着不断变化的挑战；因此，需要不断改进可再生能源领域。 因此，该提案力求解决可再生能源领域的以下关键挑战： (I)不同应用程序域中的数据密集型(或大数据)最终用户应用程序的数量正在稳步增长。然而，在RE中，当前的规范方法没有显式地捕获此类系统的数据特征。这是高效创建可靠的大数据最终用户应用程序的阻碍因素。 (Ii)在可再生能源过程中，确保系统遵守法规和标准，特别是大型、复杂的系统，到目前为止是困难、费力和容易出错的。目前用于合规性工作的RE努力评估方法是特别的，并且不可靠。这导致了几个问题，即：资源分配、产品质量、可重用性和周期时间。 这项研究很重要，因为有效的规范方法和努力估计方法将显著减少所描述的问题。反过来，这将使大数据和合规系统的用户和开发人员受益。研究人员也将受益于对可再生能源领域的知识体系的贡献。预期结果包括以下方面的新方法：指定大数据最终用户系统的质量要求，以及估计在RE中开展合规工作所需的工作量。随着加拿大企业对知识经济的推动力日益增强，拟议研究的结果将有助于宣传这一运动。