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Speculative requirements: automatic detection of uncertainty in natural language requirement

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conference contribution
posted on 2012-11-21, 14:37 authored by Hui Yang, Anne De Roeck, Vincenzo Gervasi, Alistair Willis, Bashar NuseibehBashar Nuseibeh
Stakeholders frequently use speculative language when they need to convey their requirements with some degree of uncertainty. Due to the intrinsic vagueness of speculative language, speculative requirements risk being misunderstood, and related uncertainty overlooked, and may benefit from careful treatment in the requirements engineering process. In this paper, we present a linguistically-oriented approach to automatic detection of uncertainty in natural language (NL) requirements. Our approach comprises two stages. First we identify speculative sentences by applying a machine learning algorithm called Conditional Random Fields (CRFs) to identify uncertainty cues. The algorithm exploits a rich set of lexical and syntactic features extracted from requirements sentences. Second, we try to determine the scope of uncertainty. We use a rule-based approach that draws on a set of hand-crafted linguistic heuristics to determine the uncertainty scope with the help of dependency structures present in the sentence parse tree. We report on a series of experiments we conducted to evaluate the performance and usefulness of our system.

Funding

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Directorate for Engineering

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History

Publication

Proceedings of 20th International Requirements Engineering Conference (RE'12);pp. 11-20

Publisher

IEEE Computer Society

Note

peer-reviewed

Other Funding information

EPSRC, SFI, ERC

Rights

“© 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works

Language

English

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