Natural Language Processing: Mature Enough for Requirements Documents Analysis?
Requirements engineering is the Achilles’ heel of the whole software development process, because requirements documents are often inconsistent and incomplete. Misunderstandings and errors of the requirements engineering phase propagate to later development phases and can potentially lead to a project failure.
A promising way to overcome misunderstandings is to extract and validate terms used in requirements documents and relations between these terms. This position paper gives an overview of the existing terminology extraction methods and shows how they can be integrated to reach a comprehensive text analysis approach. It shows how the integrated method would both detect inconsistencies in the requirements document and extract an ontology after elimination of inconsistencies. This integrated method would be more reliable than every of its single constituents.
KeywordsRequirement Engineering Noun Phrase Natural Language Processing Parse Tree Requirement Document
Unable to display preview. Download preview PDF.
- 2.Breitman, K.K., Sampaio do Prado Leite, J.C.: Ontology as a requirements engineering product. In: Proceedings of the 11th IEEE International Requirements Engineering Conference, pp. 309–319. IEEE Computer Society Press, Los Alamitos (2003)Google Scholar
- 3.Kof, L.: An Application of Natural Language Processing to Domain Modelling – Two Case Studies. International Journal on Computer Systems Science Engineering 20, 37–52 (2005)Google Scholar
- 4.Faure, D., Nédellec, C.: ASIUM: Learning subcategorization frames and restrictions of selection. In: Kodratoff, Y. (ed.) 10th European Conference on Machine Learning (ECML 1998) – Workshop on Text Mining, Chemnitz Germany (1998)Google Scholar
- 5.Maedche, A., Staab, S.: Discovering conceptual relations from text. In: Horn, W. (ed.) ECAI 2000. Proceedings of the 14th European Conference on Artificial Intelligence, Berlin, pp. 321–325. IOS Press, Amsterdam (2000)Google Scholar
- 6.Collins, M.: Head-Driven Statistical Models for Natural Language Parsing. PhD thesis, University of Pennsylvania (1999)Google Scholar
- 7.Ben Achour, C.: Linguistic instruments for the integration of scenarios in requirement engineering. In: Cohen, P.R., Wahlster, W. (eds.) Proceedings of the Third International Workshop on Requirements Engineering: Foundation for Software Quality (REFSQ 1997), Barcelona, Catalonia (1997)Google Scholar
- 9.Fuchs, N.E., Schwertel, U., Schwitter, R.: Attempto Controlled English (ACE) language manual, version 3.0. Technical Report 99.03, Department of Computer Science, University of Zurich (1999)Google Scholar
- 10.Preiss, J.: Choosing a parser for anaphora resolution. In: Cohen, P.R., Wahlster, W. (eds.) DAARC 2002, 4th Discourse Anaphora and Anaphor Resolution Colloquium, Lisbon, Edições Colibri, pp. 175–180 (2002)Google Scholar
- 11.Kamsties, E., Berry, D.M., Paech, B.: Detecting ambiguities in requirements documents using inspections. In: Workshop on Inspections in Software Engineering, Paris, France, pp. 68–80 (2001)Google Scholar
- 12.Nenadić, G., Spasić, I., Ananiadou, S.: Automatic discovery of term similarities using pattern mining. In: Proceedings of CompuTerm 2002, Taipei, Taiwan, pp. 43–49 (2002)Google Scholar