论文标题
Nalabs：发现自然语言要求和测试规格中的不良气味
NALABS: Detecting Bad Smells in Natural Language Requirements and Test Specifications
论文作者
论文摘要
在大规模嵌入式系统开发中，需求和测试规格通常以自然语言表示。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进行了需求审查。在需求工程过程中，低质量规格可能会产生昂贵的后果。特别是，如果在需求工程期间的反馈回路很长，导致无法容易维护的文物，难以理解并且无法移植到其他系统变体中。我们将气味的想法用于用自然语言表达的规格，定义了一组不良气味的规格。我们开发了一种称为Nalabs（自然语言不良气味）的工具，可在https://github.com/eduardenoiu/nalabs上找到，并用于自动检查规格。我们讨论了一些决定其实施和未来工作的决定。
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.
