利用自然语言处理和网络科学提取用例图元素
Maryam Imtiaz Malik1,2, Muddassar Azam Sindhu1, Rabeeh Ayaz Abbasi1
1Department of Computer Science, Quaid-i-Azam University, Islamabad, Pakistan.
PloS one
|June 23, 2023
概括
本研究介绍了一种自动化方法,用于从自然语言要求中提取软件工程用例. 这种方法显著提高了准确性,减少了软件设计中的手工工作.
科学领域:
- 软件工程 软件工程 软件工程
- 自然语言处理自然语言处理.
- 人工智能的人工智能
背景情况:
- 从自然语言要求中自动提取软件工程工件,特别是用例,仍然是一个重大挑战.
- 现有的方法往往需要人类干预,特定的形式主义,或有限的语言,限制他们的实际应用.
- 使用案例是软件设计和开发中的关键文物,指导系统功能和用户交互.
研究的目的:
- 提出并验证一种完全自动化的方法,用于从自然语言要求中提取用例,行为体及其关系.
- 克服现有的半自动化或依赖形式主义的方法的局限性.
- 为了减少人类的努力,提高软件开发生命周期的效率.
主要方法:
- 利用自然语言处理 (NLP) 技术来分析文本要求.
- 采用网络科学原理来建模和提取已识别的用例元素之间的关系.
- 开发了一条不需要人类干预或专业形式的自动化管道.
主要成果:
- 在提取用例元素时,达到约71.5% (F-Measure) 的平均精度.
- 与基线方法相比显著改善,该方法平均达到16%的准确性 (F-Measure).
- 通过几项基于文献的案例研究验证了该方法,证实了其有效性.
结论:
- 提出的自动化方法成功地从自然语言要求中提取了用例元素,并且具有很高的准确性.
- 这种方法为减少手工劳动和提高软件设计和开发效率提供了可行的解决方案.
- NLP和网络科学的整合为自动化软件文物提取提供了一个强大的框架.
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