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首页> 外文期刊>The Journal of Systems and Software >Capturing creative requirements via requirements reuse: A machine learning-based approach
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Capturing creative requirements via requirements reuse: A machine learning-based approach

机译：通过要求重用捕获创造性要求：基于机器学习的方法

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摘要

The software industry has become increasingly competitive as we see multiple software serving the same domain and striving for customers. To that end, modern software needs to provide creative features to improve sustainability. To advance software creativity, research has proposed several techniques, including multi-day workshops involving experienced requirements analysts, and semi-automated tools to support creative thinking in a limited scope. Such approaches are either useful only for software with already rich issue tracking systems, or require substantial engagement from analysts with creative minds. In a recent work, we have demonstrated a novel framework that is beneficial for both novel and existing software and allows end-to-end automation promoting creativity. The framework reuses requirements from similar software freely available online, utilizes advanced natural language processing and machine learning techniques, and leverages the concept of requirement boilerplate to generate candidate creative requirements. An application of our framework on software domains: Antivirus, Web Browser, and File Sharing followed by a human subject evaluation have shown promising results. In this invited extension, we present further analysis for our research questions and report an additional evaluation by human subjects. The results exhibit the framework's ability in generating creative features even for a relatively matured application domain, such as Web Browser, and provoking creative thinking among developers irrespective of their experience levels.
机译：当我们看到多个软件为同一领域提供多种软件并争取客户时，软件行业变得越来越竞争。为此，现代软件需要提供创造性的功能来提高可持续性。为了推进软件创造力，研究提出了几种技术，包括涉及经验丰富的需求分析师的多日研讨会，以及半自动工具，以支持有限范围的创造性思维。这些方法只适用于具有已经丰富的问题​​跟踪系统的软件，或者需要与创造性思想的分析师进行大量啮合。在最近的工作中，我们已经展示了一种新的框架，对新颖和现有软件有益，并允许促进创造力的端到端自动化。该框架重新使用在线类似软件的要求，利用先进的自然语言处理和机器学习技术，利用需求样板的概念来产生候选创新要求。我们在软件领域的框架应用：防病毒，Web浏览器和文件共享，后跟人类主题评估已经显示了有希望的结果。在这邀请的延期中，我们对我们的研究问题提供了进一步的分析，并通过人类受试者报告额外的评估。结果表明，即使对于相对成熟的应用领域，例如Web浏览器，以及如何在开发人员中引起创造性的思维，而且无论他们的体验水平如何，也表现出框架的能力。

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