@inproceedings{palshikar-etal-2019-extraction,
title = "Extraction of Message Sequence Charts from Software Use-Case Descriptions",
author = "Palshikar, Girish and
Ramrakhiyani, Nitin and
Patil, Sangameshwar and
Pawar, Sachin and
Hingmire, Swapnil and
Varma, Vasudeva and
Bhattacharyya, Pushpak",
editor = "Loukina, Anastassia and
Morales, Michelle and
Kumar, Rohit",
booktitle = "Proceedings of the 2019 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Industry Papers)",
month = jun,
year = "2019",
address = "Minneapolis, Minnesota",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/N19-2017",
doi = "10.18653/v1/N19-2017",
pages = "130--137",
abstract = "Software Requirement Specification documents provide natural language descriptions of the core functional requirements as a set of use-cases. Essentially, each use-case contains a set of actors and sequences of steps describing the interactions among them. Goals of use-case reviews and analyses include their correctness, completeness, detection of ambiguities, prototyping, verification, test case generation and traceability. Message Sequence Chart (MSC) have been proposed as a expressive, rigorous yet intuitive visual representation of use-cases. In this paper, we describe a linguistic knowledge-based approach to extract MSCs from use-cases. Compared to existing techniques, we extract richer constructs of the MSC notation such as timers, conditions and alt-boxes. We apply this tool to extract MSCs from several real-life software use-case descriptions and show that it performs better than the existing techniques. We also discuss the benefits and limitations of the extracted MSCs to meet the above goals.",
}
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%0 Conference Proceedings
%T Extraction of Message Sequence Charts from Software Use-Case Descriptions
%A Palshikar, Girish
%A Ramrakhiyani, Nitin
%A Patil, Sangameshwar
%A Pawar, Sachin
%A Hingmire, Swapnil
%A Varma, Vasudeva
%A Bhattacharyya, Pushpak
%Y Loukina, Anastassia
%Y Morales, Michelle
%Y Kumar, Rohit
%S Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Industry Papers)
%D 2019
%8 June
%I Association for Computational Linguistics
%C Minneapolis, Minnesota
%F palshikar-etal-2019-extraction
%X Software Requirement Specification documents provide natural language descriptions of the core functional requirements as a set of use-cases. Essentially, each use-case contains a set of actors and sequences of steps describing the interactions among them. Goals of use-case reviews and analyses include their correctness, completeness, detection of ambiguities, prototyping, verification, test case generation and traceability. Message Sequence Chart (MSC) have been proposed as a expressive, rigorous yet intuitive visual representation of use-cases. In this paper, we describe a linguistic knowledge-based approach to extract MSCs from use-cases. Compared to existing techniques, we extract richer constructs of the MSC notation such as timers, conditions and alt-boxes. We apply this tool to extract MSCs from several real-life software use-case descriptions and show that it performs better than the existing techniques. We also discuss the benefits and limitations of the extracted MSCs to meet the above goals.
%R 10.18653/v1/N19-2017
%U https://aclanthology.org/N19-2017
%U https://doi.org/10.18653/v1/N19-2017
%P 130-137
Markdown (Informal)
[Extraction of Message Sequence Charts from Software Use-Case Descriptions](https://aclanthology.org/N19-2017) (Palshikar et al., NAACL 2019)
ACL
- Girish Palshikar, Nitin Ramrakhiyani, Sangameshwar Patil, Sachin Pawar, Swapnil Hingmire, Vasudeva Varma, and Pushpak Bhattacharyya. 2019. Extraction of Message Sequence Charts from Software Use-Case Descriptions. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Industry Papers), pages 130–137, Minneapolis, Minnesota. Association for Computational Linguistics.