Unpacking Ambiguity in Building Requirements to Support Automated Compliance Checking

In the architecture, engineering, and construction (AEC) industry, manual compliance checking is labor-intensive, time-consuming, expensive, and error-prone. Automated compliance checking (ACC) has been extensively studied in the past 50 years to improve the productivity and accuracy of the compliance checking process. While numerous ACC systems have been proposed, these systems can only deal with requirements that include quantitative metrics or specified properties. This leaves the remaining 53% of building requirements to be checked manually, mainly due to the ambiguity embedded in them. In the literature, little is known about the ambiguity of building requirements, which impedes their accurate interpretation and automated checking. This research thus aims to address this issue and establish a taxonomy of ambiguity. Building requirements in health building notes (HBNs) are analyzed using an inductive approach. The results show that some ambiguous clauses in building requirements reflect regulators’ intention while others are unintentional, resulting from the use of language, tacit knowledge, and ACC-specific reasons. This research is valuable for compliance-checking researchers and practitioners because it unpacks ambiguity in building requirements, laying a solid foundation for addressing ambiguity appropriately

On the role of ambiguity in RE

[Context and motivation] Ambiguity has long been pictured as one of the worst enemies of the specifier, especially with reference to ambiguity in natural language (NL) requirements specifications. [Question/problem] In this paper, we investigate the nature of ambiguity, and [Principal ideas/result] advocate that the simplistic view of ambiguity as merely a "defect" that has to be avoided at all costs does not do justice to the complexity of this phenomenon. We also provide a finer classification of several types of ambiguities, distinguishing their different causes and effects in the development process. [Contribution] This better understanding can help in the analysis of practical experiences and in the design of more effective methods to detect, mark and handle ambiguity. © 2010 Springer-Verlag