论文标题
需求工程的自然语言处理(NLP):系统地图研究
Natural Language Processing (NLP) for Requirements Engineering: A Systematic Mapping Study
论文作者
论文摘要
自然语言处理支持的需求工程是一个研究和开发领域,试图将NLP技术,工具和资源应用于各种要求文档或工件,以支持在各个阶段执行的一系列语言分析任务。此类任务包括检测语言问题,确定关键领域概念并在需求之间建立可追溯性联系。本文调查了NLP4RE研究的景观,以了解最新技术的状态并确定开放问题。系统的映射研究方法用于进行这项调查,该调查确定了404项相关的基本研究,并根据五个研究问题对它们进行了审查,介绍了NLP4RE研究的五个方面,涉及文献,经验研究状态,研究重点,实践状态,实践状态以及使用的NLP技术。结果:1)NLP4RE是RE的一个积极蓬勃发展的研究领域,它积累了大量出版物,并引起了不同社区的广泛关注; 2)大多数NLP4RE研究是仅使用实验室实验或示例应用的解决方案建议; 3)大多数研究都集中在分析阶段,检测是其中央语言分析任务和要求规范作为其常用文档类型; 4)已经提出了130个新工具来支持一系列语言分析任务,但从长远来看,尽管已经发布了一些工业应用,但从长远来看很少。 5)从选定的研究中提取140个NLP技术,66个NLP工具和25个NLP资源。
Natural language processing supported requirements engineering is an area of research and development that seeks to apply NLP techniques, tools and resources to a variety of requirements documents or artifacts to support a range of linguistic analysis tasks performed at various RE phases. Such tasks include detecting language issues, identifying key domain concepts and establishing traceability links between requirements. This article surveys the landscape of NLP4RE research to understand the state of the art and identify open problems. The systematic mapping study approach is used to conduct this survey, which identified 404 relevant primary studies and reviewed them according to five research questions, cutting across five aspects of NLP4RE research, concerning the state of the literature, the state of empirical research, the research focus, the state of the practice, and the NLP technologies used. Results: 1) NLP4RE is an active and thriving research area in RE that has amassed a large number of publications and attracted widespread attention from diverse communities; 2) most NLP4RE studies are solution proposals having only been evaluated using a laboratory experiment or an example application; 3) most studies have focused on the analysis phase, with detection as their central linguistic analysis task and requirements specification as their commonly processed document type; 4) 130 new tools have been proposed to support a range of linguistic analysis tasks, but there is little evidence of adoption in the long term, although some industrial applications have been published; 5) 140 NLP techniques, 66 NLP tools and 25 NLP resources are extracted from the selected studies.