TY - GEN
T1 - Automated Mining and Checking of Formal Properties in Natural Language Requirements
AU - Pi, Xingxing
AU - Shi, Jianqi
AU - Huang, Yanhong
AU - Wei, Hansheng
N1 - Publisher Copyright:
© 2019, Springer Nature Switzerland AG.
PY - 2019
Y1 - 2019
N2 - Bridging the gap between natural language requirements (NLR) and precise formal specifications is a crucial task of knowledge engineering. Software system development has become more complex in recent years, and it includes many requirements in different domains that users need to understand. Many of these requirements are expressed in natural language, which may be incomplete and ambiguous. However, the formal language with its rigorous semantics may accurately represent certain temporal logic properties and allow for automatic validation analysis. It is difficult for software engineers to understand the formal temporal logic from numerous requirements. In this paper, we propose a novel method to automatically mine the linear temporal logic (LTL) from the natural language requirements and check the consistency among different formal properties. We use natural language processing (NLP) to parse requirement sentences and map syntactic dependencies to LTL formulas by using our extraction rules. Also, we apply the automata-based model checking to assess the correctness and consistency of the extracted properties. Through implementation and case studies, we demonstrate that our approach is well suited to deal with the temporal logic requirements upon which the natural language is based.
AB - Bridging the gap between natural language requirements (NLR) and precise formal specifications is a crucial task of knowledge engineering. Software system development has become more complex in recent years, and it includes many requirements in different domains that users need to understand. Many of these requirements are expressed in natural language, which may be incomplete and ambiguous. However, the formal language with its rigorous semantics may accurately represent certain temporal logic properties and allow for automatic validation analysis. It is difficult for software engineers to understand the formal temporal logic from numerous requirements. In this paper, we propose a novel method to automatically mine the linear temporal logic (LTL) from the natural language requirements and check the consistency among different formal properties. We use natural language processing (NLP) to parse requirement sentences and map syntactic dependencies to LTL formulas by using our extraction rules. Also, we apply the automata-based model checking to assess the correctness and consistency of the extracted properties. Through implementation and case studies, we demonstrate that our approach is well suited to deal with the temporal logic requirements upon which the natural language is based.
UR - https://www.scopus.com/pages/publications/85077116773
U2 - 10.1007/978-3-030-29563-9_8
DO - 10.1007/978-3-030-29563-9_8
M3 - 会议稿件
AN - SCOPUS:85077116773
SN - 9783030295622
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 75
EP - 87
BT - Knowledge Science, Engineering and Management - 12th International Conference, KSEM 2019, Proceedings
A2 - Douligeris, Christos
A2 - Apostolou, Dimitris
A2 - Karagiannis, Dimitris
PB - Springer
T2 - 12th International Conference on Knowledge Science, Engineering and Management, KSEM 2019
Y2 - 28 August 2019 through 30 August 2019
ER -