NALABS：检测自然语言需求和测试规范中的不良气味
NALABS: Detecting Bad Smells in Natural Language Requirements and Test Specifications
摘要：
在大规模嵌入式系统的开发中，需求和测试规范往往是用自然语言来表达的。在开发此类产品的背景下，在许多情况下，使用这些规格作为质量保证的基础手动进行需求审查。低质量的规格在需求工程过程中可能会产生昂贵的后果。特别是，如果需求工程期间的反馈循环很长，导致工件不容易维护，难以理解，并且无法有效地移植到其他系统变体。我们将气味的概念用于用自然语言表达的规范，定义了一组用于难闻气味的规范。我们开发了一个名为NALABS（自然语言不良气味）的工具，可在https://github.com/eduardenoiu/NALABS上获得，用于自动检查规格。我们讨论了一些决定，其实施和未来的工作。
英文摘要：
In large-scale embedded system development, requirement and test specifications are often expressed in natural language. In the context of developing such products, requirement review is performed in many cases manually using these specifications as a basis for quality assurance. Low-quality specifications can have expensive consequences during the requirement engineering process. Especially, if feedback loops during requirement engineering are long, leading to artifacts that are not easily maintainable, are hard to understand, and are inefficient to port to other system variants. We use the idea of smells to specifications expressed in natural language, defining a set of specifications for bad smells. We developed a tool called NALABS (NAtural LAnguage Bad Smells), available on https://github.com/eduardenoiu/NALABS and used for automatically checking specifications. We discuss some of the decisions made for its implementation, and future work.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
