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Taming Ambiguity in Natural Language Requirements

: Kamsties, E.; Paech, B.

13th International Conference Software and Systems Engineering and their Applications, ICSSEA 2000. Proceedings. Vol.2
Paris, 2000
8 S. : Ill., Lit.
International Conference Software and Systems Engineering and their Applications (ICSSAE) <13, 2000, Paris>
Fraunhofer IESE ()
natural language requirement; ambiguity; metamodel; requirements specification; reading technique; inspection

One of the main tasks of requirements engineering (RE) is the creation of a requirements document that precisely, consistently, and completely describes the functional and non-functional properties of the system to be built. At some point during the RE process, the requirements are written down using a natural language or a requirements specification language. On one hand, natural language is flexible, universal, and wide-spread. On the other hand, natural language requirements are recognized widely as being incomplete, inconsistent, and inherently ambiguous. Semi-formal and formal requirements specification techniques, such as UML or SCR, have been proposed to overcome these deficiencies. Completeness and consistency of these specifications can be tackled to some degree mechanically by tools. However, as a recent study shows, ambiguity rarely surfaces during the development of a requirements model. Thus,since a requirements specification technique enforces precision, the resulting requirements model becomes unambiguously wrong.
In this paper, we show how to detect ambiguities in natural language requirements using a checklist. We distinguish between linguistic and RE-specific ambiguities. Linguistic ambiguities are those ambiguities that are usually discussed in RE textbooks such as ambiguous pronoun references. RE-specific ambiguities occur with respect to the RE context, which includes the application domain and the system domain. For example, the requirement "If the bank customer maintains a minimum balance in his or her checking account, there is no monthly service charge" is ambiguous not because of its linguistic representation, but because of the operational environment and application domain. In the requirements documents that we have investigated, RE-specific ambiguities account for the majority of ambiguities, while pure linguistic ambiguities played a less significant role.
In this paper, we present also an approach that allows identifying types of RE-specific ambiguity from a metamodel, e.g., of a requirements specification technique. Based on the identified types of ambiguity, we have developed an improved inspection technique for natural language requirements on the basis of checklists and scenario-based reading.