Extracting and Classifying Requirements from Software Engineering Contracts

被引:27
|
作者
Sainani, Abhishek [1 ]
Anish, Preethu Rose [1 ]
Joshi, Vivek [1 ]
Ghaisas, Smita [1 ]
机构
[1] TCS Res, Pune, Maharashtra, India
关键词
Software engineering contracts; requirements; deep learning; extraction; classification;
D O I
10.1109/RE48521.2020.00026
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, we present our work on extracting and classifying requirements from large software engineering contracts. Typically, the process of requirements elicitation begins after a contractual agreement is signed by all participants. Our interactions with the legal compliance team in a large vendor organization reveal that business contracts can help in the identification of high-level requirements relevant to the success of software engineering projects. We posit that requirements engineering as a discipline has an even wider scope than software engineering of which it is traditionally considered to be a sub-discipline. This is because software engineering-specific requirements are but a part of the success story of any large project. The requirements that emerge from contracts are obligatory in nature, whether or not they pertain to core software development. Therefore, it is important that these are extracted and classified for the benefit of software engineers and other stakeholders responsible for a project. We discuss the results of an exploratory study and a range of experiments from the use of regular expressions to Bidirectional Encoder Representations from Transformers for automating the extraction and classification of requirements from software engineering contracts. With Bidirectional Encoder Representations from Transformers, we obtained a high f-score of greater than eighty four percent for classification of requirements.
引用
收藏
页码:147 / 157
页数:11
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