Using Commonsense Knowledge and Text Mining for Implicit Requirements Localization

Emebo Onyeka; Aparna S. Varde; Vaibhav Anu; Niket Tandon; Olawande Daramola

doi:10.1109/ICTAI50040.2020.00146

Using Commonsense Knowledge and Text Mining for Implicit Requirements Localization

Emebo Onyeka, Aparna S. Varde, Vaibhav Anu, Niket Tandon, Olawande Daramola

Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

This paper addresses identification of implicit requirements (IMRs) in software requirements specifications (SRS). IMRs, as opposed to explicit requirements, are not specified by users but are more subtle. It has been noticed that IMRs are crucial to the success of software development. In this paper, we demonstrate a software tool called COTIR developed by us as a system that integrates Commonsense knowledge, Ontology and Text mining for early identification of Implicit Requirements. This relieves human software engineers from the tedious task of manually identifying IMRs in huge SRS documents. Our evaluation reveals that COTIR outperforms existing IMR tools. This demo paper would be useful to Software Engineers since it deals with automation in the requirements analysis phase, thus contributing to Requirements Engineering. It would interest AI scientists as it entails multi-disciplinary work encompassing text mining, ontology and commonsense knowledge. It makes a broader impact on Smart Cities, because automated identification of IMRs would offer inputs to Smart City Tools, where requirements may often be implicit given that Smart Cities are an emerging and growing paradigm.

Original language	English
Title of host publication	Proceedings - IEEE 32nd International Conference on Tools with Artificial Intelligence, ICTAI 2020
Editors	Miltos Alamaniotis, Shimei Pan
Publisher	IEEE Computer Society
Pages	935-940
Number of pages	6
ISBN (Electronic)	9781728192284
DOIs	https://doi.org/10.1109/ICTAI50040.2020.00146
State	Published - Nov 2020
Event	32nd IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2020 - Virtual, Baltimore, United States Duration: 9 Nov 2020 → 11 Nov 2020

Publication series

Name	Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI
Volume	2020-November
ISSN (Print)	1082-3409

Conference

Conference	32nd IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2020
Country	United States
City	Virtual, Baltimore
Period	9/11/20 → 11/11/20

Keywords

AI in Smart Cities
Commonsense Knowledge
Implicit Requirements
Ontology
Requirements Engineering
Software Demo
Text Mining

Access to Document

10.1109/ICTAI50040.2020.00146

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Onyeka, E., Varde, A. S., Anu, V., Tandon, N., & Daramola, O. (2020). Using Commonsense Knowledge and Text Mining for Implicit Requirements Localization. In M. Alamaniotis, & S. Pan (Eds.), Proceedings - IEEE 32nd International Conference on Tools with Artificial Intelligence, ICTAI 2020 (pp. 935-940). [9288192] (Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI; Vol. 2020-November). IEEE Computer Society. https://doi.org/10.1109/ICTAI50040.2020.00146

Onyeka, Emebo ; Varde, Aparna S. ; Anu, Vaibhav ; Tandon, Niket ; Daramola, Olawande. / Using Commonsense Knowledge and Text Mining for Implicit Requirements Localization. Proceedings - IEEE 32nd International Conference on Tools with Artificial Intelligence, ICTAI 2020. editor / Miltos Alamaniotis ; Shimei Pan. IEEE Computer Society, 2020. pp. 935-940 (Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI).

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abstract = "This paper addresses identification of implicit requirements (IMRs) in software requirements specifications (SRS). IMRs, as opposed to explicit requirements, are not specified by users but are more subtle. It has been noticed that IMRs are crucial to the success of software development. In this paper, we demonstrate a software tool called COTIR developed by us as a system that integrates Commonsense knowledge, Ontology and Text mining for early identification of Implicit Requirements. This relieves human software engineers from the tedious task of manually identifying IMRs in huge SRS documents. Our evaluation reveals that COTIR outperforms existing IMR tools. This demo paper would be useful to Software Engineers since it deals with automation in the requirements analysis phase, thus contributing to Requirements Engineering. It would interest AI scientists as it entails multi-disciplinary work encompassing text mining, ontology and commonsense knowledge. It makes a broader impact on Smart Cities, because automated identification of IMRs would offer inputs to Smart City Tools, where requirements may often be implicit given that Smart Cities are an emerging and growing paradigm.",

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author = "Emebo Onyeka and Varde, {Aparna S.} and Vaibhav Anu and Niket Tandon and Olawande Daramola",

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Onyeka, E, Varde, AS , Anu, V, Tandon, N & Daramola, O 2020, Using Commonsense Knowledge and Text Mining for Implicit Requirements Localization. in M Alamaniotis & S Pan (eds), Proceedings - IEEE 32nd International Conference on Tools with Artificial Intelligence, ICTAI 2020., 9288192, Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI, vol. 2020-November, IEEE Computer Society, pp. 935-940, 32nd IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2020, Virtual, Baltimore, United States, 9/11/20. https://doi.org/10.1109/ICTAI50040.2020.00146

Using Commonsense Knowledge and Text Mining for Implicit Requirements Localization. / Onyeka, Emebo; Varde, Aparna S.; Anu, Vaibhav; Tandon, Niket; Daramola, Olawande.

Proceedings - IEEE 32nd International Conference on Tools with Artificial Intelligence, ICTAI 2020. ed. / Miltos Alamaniotis; Shimei Pan. IEEE Computer Society, 2020. p. 935-940 9288192 (Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI; Vol. 2020-November).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Onyeka E, Varde AS , Anu V, Tandon N, Daramola O. Using Commonsense Knowledge and Text Mining for Implicit Requirements Localization. In Alamaniotis M, Pan S, editors, Proceedings - IEEE 32nd International Conference on Tools with Artificial Intelligence, ICTAI 2020. IEEE Computer Society. 2020. p. 935-940. 9288192. (Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI). https://doi.org/10.1109/ICTAI50040.2020.00146