计算机应用与软件2024，Vol.41Issue(11)：78-85,8.DOI:10.3969/j.issn.1000-386x.2024.11.011
针对需求缺陷检测任务的自然语言需求数据集评估
NATURAL LANGUAGE REQUIREMENT DATASET EVALUATION FOR REQUIREMENT DEFECT DETECTION TASK
摘要
Abstract
Natural language has been widely used as one form of software requirements as it is easy to understand.But natural language requirements are prone to defects.At present,applying natural language processing techniques on requirement defects has gradually become a research hotspot.However,unlike other fields having a large number of publicly available datasets,in the field of software engineering,there is still a lack of suitable datasets and methods to evaluate whether datasets are sufficient for helping perform tasks such as natural language defect detection.Aiming at the task of requirement defect detection,we propose an evaluation method and quantitative metric model for corresponding dataset,and designe a rule-based evaluation framework.We experimented with existing public requirement dataset,and conducted statistics based on quantitative metrics.关键词
软件需求/需求缺陷/需求工程/自然语言处理Key words
Software requirement/Requirement defect/Requirement engineering/Natural language processing分类
信息技术与安全科学引用本文复制引用
蔡一涵,马立鹏,杨卫东,施伯乐..针对需求缺陷检测任务的自然语言需求数据集评估[J].计算机应用与软件,2024,41(11):78-85,8.基金项目
国家自然科学基金项目(U2033209). （U2033209）
