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Reasoning about inconsistencies in natural language requirements

Authors:

Vincenzo Gervasi and

Didar ZowghiAuthors Info & Claims

ACM Transactions on Software Engineering and Methodology (TOSEM), Volume 14, Issue 3

Pages 277 - 330

https://doi.org/10.1145/1072997.1072999

Published: 01 July 2005 Publication History

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Abstract

The use of logic in identifying and analyzing inconsistency in requirements from multiple stakeholders has been found to be effective in a number of studies. Nonmonotonic logic is a theoretically well-founded formalism that is especially suited for supporting the evolution of requirements. However, direct use of logic for expressing requirements and discussing them with stakeholders poses serious usability problems, since in most cases stakeholders cannot be expected to be fluent with formal logic. In this article, we explore the integration of natural language parsing techniques with default reasoning to overcome these difficulties. We also propose a method for automatically discovering inconsistencies in the requirements from multiple stakeholders, using both theorem-proving and model-checking techniques, and show how to deal with them in a formal manner. These techniques were implemented and tested in a prototype tool called CARL. The effectiveness of the techniques and of the tool are illustrated by a classic example involving conflicting requirements from multiple stakeholders.

References

[1]

Abiteboul, S. and Simon, E. 1991. Fundamental properties of deterministic and nondeterministic extensions of Datalog. Theoret. Comput. Sci. 78, 1, 137--158.

Digital Library

Google Scholar

[2]

Alchourrón, C. E., Gärdenfors, P., and Makinson, D. 1985. On the logic of theory change: Partial meet contraction and revision functions. J. Symbol. Logic 50, 510--530.

Crossref

Google Scholar

[3]

Ali, S. 1994. A logical language for natural language processing. In Proceedings of the 10th Biennial Canadian Artifical Intelligence Conference (Banff, Alta., Canada). 187--196.

Google Scholar

[4]

Ambriola, V. and Gervasi, V. 1999. Experiences with domain-based parsing of natural language requirements. In Proceedings of the Fourth International Conference on Applications of Natural Language to Information Systems, G. Fliedl and H. C. Mayr, Eds. OCG Schriftenreihe (Lecture Notes), no. 129. OGC, Klagenfurt, Austria, 145--148.

Google Scholar

[5]

Balzer, R. 1991. Tolerating inconsistency. In Proceedings of the 13th International Conference on Software Engineering (ICSE-13). IEEE Computer Society Press, Los Alamitos, CA, 158--165.

Digital Library

Google Scholar

[6]

Berry, D. M., Kamsties, E., and Krieger, M. M. 2003. From contract drafting to software specification: Linguistic sources of ambiguity---a handbook. (unpublished as of July 2005, but available on-line at http://se.uwaterloo.ca/&sim;dberry/handbook/ambiguityHandbook.pdf).

Google Scholar

[7]

Boehm, B. W. 1976. Software engineering. IEEE Trans. Comput. 25, 12 (Dec.), 1226--1241.

Google Scholar

[8]

CHAOS. 1995. Software development report by the Standish group. Available online at http://www.standishgroup.com/chaos.html.

Google Scholar

[9]

Chechik, M., Devereux, B., Easterbrook, S., and Gurfinkel, A. 2003. Multi-valued symbolic model-checking. ACM Trans. Softw. Eng. Methodol. 12, 4 (Oct.), 371--408.

Digital Library

Google Scholar

[10]

Choi, Y., Rayadurgam, S., and Heimdahl, M. P. E. 2002. Toward automation for model-checking requirements specifications with numeric constraints. Requirements Eng. J. 7, 4 (Dec.), 225--242.

Crossref

Google Scholar

[11]

Clarke, E. M., Emerson, E. A., and Sisla, A. P. 1986. Automatic verification of finite-state concurrent systems using temporal logic specifications. ACM Trans. Programm. Lang. Syst. 8, 2, 244--263.

Digital Library

Google Scholar

[12]

Dalianis, H. 1992. A method for validating a conceptual model by natural language discourse generation. In Advanced Information Systems Engineering. Lecture Notes in Computer Science, vol. 593. Springer-Verlag, Berlin, Germany.

Google Scholar

[13]

Daly, E. 1977. Management of software development. IEEE Trans. Softw. Eng. 3, 3 (May), 229--242.

Google Scholar

[14]

Davis, A. M., Jordan, K., and Nakajima, T. 1997. Elements underlying the specification of requirements. Ann. Softw. Eng. 3, 63--100. (Special issue on Software Requirements Engineering)

Digital Library

Google Scholar

[15]

Easterbrook, S. and Chechik, M. 2002. Guest editorial: Special issue on model checking in requirements engineering. Requirements Eng. J. 7, 4 (Dec.), 221--224.

Crossref

Google Scholar

[16]

Easterbrook, S. and Nuseibeh, B. 1996. Using viewpoints for inconsistency management. IEE Softw. Eng. J. 11, 1, 31--43.

Crossref

Google Scholar

[17]

Eshuis, R., Jansen, D. N., and Wieringa, R. 2002. Requirements-level semantics and model checking of object-oriented statecharts. Requirements Eng. J. 7, 4 (Dec.), 243--263.

Crossref

Google Scholar

[18]

Fantechi, A., Gnesi, S., Ristori, G., Carenini, M., Vanocchi, M., and Moreschini, P. 1994. Assisting requirement formalization by means of natural language translation. Form. Meth. Syst. Des. 4, 3, 243--263.

Digital Library

Google Scholar

[19]

Finkelstein, A. and Dowell, J. 1996. A comedy of errors: The London Ambulance Service case study. In Proceedings of the 8th International Workshop on Software Specification & Design. IEEE Computer Society Press, Los Alamitos, CA, 2--4.

Digital Library

Google Scholar

[20]

Finkelstein, D., Gabbay, A., Hunter, J., Kramer, B., and Nuseibeh, A. 1994. Inconsistency handling in multiperspective specifications. IEEE Trans. Softw. Eng. 20, 8, 569--577.

Digital Library

Google Scholar

[21]

Fuchs, N. E. and Schwitter, R. 1995. Specifying logic programs in controlled natural language. In Proceedings of the Workshop on Computational Logic for Natural Language Processing (University of Edinburgh, Edinburgh, Scotland).

Google Scholar

[22]

Gabbay, D. and Hunter, A. 1991. Making inconsistency respectable: A logical framework for inconsistency in reasoning, Part 1---a position paper. In Proceedings of Fundamentals AI Research. Lecture Notes in Computer Science, vol. 535. Springer-Verlag, New York, 19--32.

Digital Library

Google Scholar

[23]

Garcez, A., Russo, A., Nuseibeh, B., and Kramer, J. 2003. Combining abductive reasoning and inductive learning to evolve requirements specifications. IEE Proc.---Softw. 150, 1 (Feb.), 25--38.

Google Scholar

[24]

Gärdenfors, P. 1988. Knowledge in Flux: Modeling the Dynamics of Epistemic States. MIT Press, Cambridge, MA.

Google Scholar

[25]

Gärdenfors, P. and Rott, H. 1995. Belief revision. In Handbook of Logic in Artificial Intelligence and Logic Programming Volume IV: Epistemic and Temporal Reasoning, D. M. Gabbay, C. J. Hogger, and J. A. Robinson, Eds. Oxford University Press, Oxford, U.K. 35--132.

Digital Library

Google Scholar

[26]

Gervasi, V. 2000. Environment support for requirements writing and analysis. Ph.D. dissertation. University of Pisa, Pisa, Italy.

Google Scholar

[27]

Gervasi, V. 2001. The Cico domain-based parser. Tech. rep. TR-01-25. Dipartimento di Informatica, University of Pisa, Pisa, Italy.

Digital Library

Google Scholar

[28]

Gervasi, V. and Ambriola, V. 2002. Quantitative assessment of textual complexity. In Complexity in Language and Text, L. Merlini Barbaresi, Ed. PLUS-University of Pisa, Pisa, Italy, 197--228.

Google Scholar

[29]

Gervasi, V. and Nuseibeh, B. 2002. Lightweight validation of natural language requirements. Softw.: Pract. Exper. 32, 2 (Feb.), 113--133.

Digital Library

Google Scholar

[30]

Ghezzi, C. and Nuseibeh, B. 1998. Introduction to the special section on managing inconsistency in software development. IEEE Trans. Softw. Eng. 24, 11 (Nov.), 906--907.

Digital Library

Google Scholar

[31]

Ghose, A. K. 1995. Practical belief change. Ph.D. dissertation. Department of Computing Science, University of Alberta, Edmonton, Alta., Canada.

Digital Library

Google Scholar

[32]

Harper, W. L. 1977. Rational conceptual change. In PSA 1976 East Lansing, Mich.: Philosophy of Science Association, vol. 2. Philosophy of Science Association, East Lansing, MI, 462--494.

Google Scholar

[33]

Hars, A. 1996. Advancing CASE productivity by using natural language processing and computerized ontologies: The ACAPULCO system. In Proceedings of the Eleventh Automated Software Engineering Conference.

Google Scholar

[34]

Hunter, A. and Nuseibeh, B. 1998. Managing inconsistent specifications: Reasoning, analysis and action. Trans. Softw. Eng. Method. 7, 4 (Oct.), 335--367.

Digital Library

Google Scholar

[35]

Huth, M. and Pradhan, S. 2004. Consistent partial model checking. Electron. Notes Theoret. Comput. Sci. 73, 45--85. (Proceedings of the Workshop on Domains VI.)

Digital Library

Google Scholar

[36]

Ibanez, M. 1996. European user survey analysis. Tech. rep. ESI report TR95104. European Software Institute, Zamudio, Spain. Web site: www.esi.es.

Google Scholar

[37]

Jackson, D. 2000. Automating first-order relational logic. In Proceedings of the 8th International Symposium on Foundations of Software Engineering (FSE8).

Digital Library

Google Scholar

[38]

Juristo, N., Moreno, A. M., and López, M. 2000. How to use linguistic instruments for object-oriented analysis. IEEE Softw. 17, 3 (May/June), 80--89.

Digital Library

Google Scholar

[39]

Kowalski, R. 1979. Logic for Problem Solving. North Holland Elsevier, New York, NY.

Digital Library

Google Scholar

[40]

Levi, I. 1977. Subjunctives, dispositions and chances. Synthese 34, London, U.K., 423--455.

Google Scholar

[41]

Macias, B. and Pulman, S. G. 1993. Natural Language Processing for Requirements Specification. Chapman and Hall, London, U.K., 57--89.

Google Scholar

[42]

Makinson, D. 1985. How to give it up: A survey of some formal aspects of the logic of theory change. Synthese 62, 4, 347--363.

Crossref

Google Scholar

[43]

Marcus, M. P., Santorini, B., and Marcinkiewicz, M. A. 1993. Building a large annotated corpus of English: The Penn Treebank. Computa. Linguist. 19, 313--330.

Digital Library

Google Scholar

[44]

Mich, L. 1996. NL-OOPS: From natural language requirements to object oriented requirements using the natural language processing system LOLITA. J. Natural Lang. Eng. 2, 2, 161--187.

Digital Library

Google Scholar

[45]

Mich, L., Franch, M., and Novi Inverardi, P. 2004. Market research for requirements analysis using linguistic tools. Requirements Eng. J. 9, 1, 40--56.

Digital Library

Google Scholar

[46]

Nebel, B. 1991. Belief revision and default reasoning: Syntax-based approaches. In Proceedings of the Second International Conference on Principles of Knowledge Representation and Reasoning. 417--428.

Google Scholar

[47]

Neill, C. J. and Laplante, P. A. 2003. Requirements engineering: The state of the practice. IEEE Softw. 20, 6 (Nov./Dec.), 40--45.

Digital Library

Google Scholar

[48]

Nuseibeh, B. 1996. To be and not to be: On managing inconsistency in software development. In Proceedings of the IEEE International Workshop on Software Specification and Design (IWSSD-8). IEEE Computer Society Press, Los Alamitos, CA, 164--169.

Digital Library

Google Scholar

[49]

Poole, D. 1988. A logical framework for default reasoning. Art. Intell. 36, 27--47.

Digital Library

Google Scholar

[50]

Poole, D., Goebel, R., and Aleliunas, R. 1987. Theorist: A logical reasoning system for defaults and diagnosis. In The Knowledge Frontier: Essays in the Representation of Knowledge, N. Cercone and G. McCalla, Eds. Springer Verlag, Berlin, Germany, 331--352.

Google Scholar

[51]

Reeves, S. and Clarke, M. 1990. Logic for Computer Science. Addison-Wesley, Reading, MA.

Google Scholar

[52]

Rolland, C. and Proix, C. 1992. A natural language approach for requirements engineering. In Proceedings of the Fourth International Conference CAiSE'92 on Advanced Information Systems Engineering, P. Loucopoulos, Ed. Lecture Notes in Computer Science, vol. 593. Springer-Verlag, Berlin, Germany, 257--277.

Google Scholar

[53]

Russo, A., Miller, R., Nuseibeh, B., and Kramer, J. 2002. An abductive approach for analysing event-based requirements specifications. In Proceedings of the 18th International Conference on Logic Programming (Copenhagen, Denmark).

Digital Library

Google Scholar

[54]

Russo, A. and Nuseibeh, B. 2001. On the use of logical abduction in software engineering. In Handbook of Software Engineering and Knowledge Engineering, S. K. Chang, Ed. World Scientific Publishing, Singapore.

Google Scholar

[55]

Ryan, M. D. 1993. Defaults in specifications. In Proceedings of the IEEE International Symposium on Requirements Engineering (RE93). 142--149.

Google Scholar

[56]

Sadri, F. and Kowalski, R. 1986. An application of general theorem proving to database integrity. Tech. rep. Department of Computing, Imperial College, London, U.K.

Google Scholar

[57]

Schmid, H. 1994. Probabilistic part--of--speech tagging using decision trees. In Proceedings of the Conference on New Methods in Language Processing (Manchester, U.K.). 44--49.

Google Scholar

[58]

Tsai, J. P., Weigert, T., and jang, H. C. 1992. A hybrid knowledge representation as a basis of requirements specification and specification analysis. IEEE Trans. Softw. Eng. 18, 12, 1076--1100.

Digital Library

Google Scholar

[59]

Ullman, J. D. 1989. Principles of Database and Knowledge-Base Systems, Vols. I and II. Computer Science Press, Rockville, MD.

Digital Library

Google Scholar

[60]

van Lamsweerde, A. 2000. Formal specifications: A roadmap. In The Future of Software Engineering. ACM Press, New York, NY, 149--159. (Proceedings of the 22nd IEEE International Conference on Software Engineering.)

Digital Library

Google Scholar

[61]

Webber, B. L. 1983. So what can we talk about now. In Computational Models of Discourse, M. Brady and B. Berwick, Eds. MIT Press, Cambridge, MA, 331--370.

Google Scholar

[62]

Zave, P. and Jackson, M. 1997. Four dark corners of requirements engineering. ACM Trans. Softw. Eng. Method. 6, 1, 1--30.

Digital Library

Google Scholar

[63]

Zowghi, D. 1999. A logic-based framework for the management of changing software requirements. Ph.D. dissertation. Macquarie University, Sydney, Australia.

Google Scholar

[64]

Zowghi, D. and Gervasi, V. 2004. On the interplay between consistency, completeness, and correctness in requirements evolution. Informat. Softw. Techn. 46, 11 (Sept.), 763--779.

Crossref

Google Scholar

[65]

Zowghi, D., Gervasi, V., and McRae, A. 2001. Using default reasoning to discover inconsistencies in natural language requirements. In Proceedings of the 8th Asia-Pacific Software Engineering Conference. 133--140.

Digital Library

Google Scholar

[66]

Zowghi, D., Ghose, A., and Offen, R. 1997. Computer-assisted requirements evolution tool: Formal foundations and architecture. In Proceedings of the 2nd Australian Workshop on Requirements Engineering (AWRE97, Sydney, Australia). 47--59.

Google Scholar

[67]

Zowghi, D., Ghose, A., and Peppas, P. 1996. A framework for reasoning about requirements evolution. In Proceedings of the 4th Pacific Rim International Conference on Artificial Intelligence (PRICAI'96). 157--168.

Digital Library

Google Scholar

[68]

Zowghi, D. and Offen, R. 1997. A logical framework for modelling and reasoning about the evolution of requirements. In Proceedings of the Third IEEE International Symposium on Requirements Engineering (RE97). 247--259.

Digital Library

Google Scholar

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Reviewer: Gilbert Babin

A fundamental problem in requirements engineering (RE) is to make the transition from the informal description of requirements on the real-life system to the formal representation of these requirements. Furthermore, even if formalization was easily done, most users find it difficult to understand a formal representation of these requirements. In a very thorough paper, Gervasi and Zowghi propose a pragmatic, yet formal, solution to the problem. They propose the use of propositional logic as the internal representation of the requirements, while using natural language as the external representation. This implies that parsing and unparsing methods are defined to convert natural language phrases into propositional logic, and vice versa. Although the authors only conjecture that the parsing and unparsing methods are correct, they provide a field study (in the appendix) to support this claim. Their use of the belief revision theory enables their system, called CARL, to manage inconsistencies that may appear as new requirements are added. Assertions may be categorized as facts (that always hold), hypotheses (possibly true), and constraints (always false). Inserting a new assertion may force other assertions to become hypotheses, as the new assertion creates inconsistencies. Throughout the paper, they provide very illustrative examples that really help the reader understand the approach. In particular, they provide a complete (yet simple) example using the CARL prototype. Online Computing Reviews Service

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cover image ACM Transactions on Software Engineering and Methodology

ACM Transactions on Software Engineering and Methodology Volume 14, Issue 3

July 2005

134 pages

ISSN:1049-331X

EISSN:1557-7392

DOI:10.1145/1072997

Issue’s Table of Contents

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Using Default Reasoning to Discover Inconsistencies in Natural Language Requirements

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