Clustering-Based Approach for Building Code Computability Analysis
Publication: Journal of Computing in Civil Engineering
Volume 35, Issue 6
Abstract
One common limitation of all automated code compliance-checking methods and tools is their inability to deal with all types of building-code requirements. More research is needed to better identify the different types of requirements, in terms of their syntactic and semantic structures and complexities, to gain more insights about the capabilities and limitations of existing methods and tools (i.e., which requirements they can automatically process, represent, or check, and which not). To address this need, this paper proposes a new set of syntactic and semantic features and complexity and computability metrics for code computability analysis. A clustering-based approach was used to identify the different types of code sentences, in terms of their computability, using the proposed features and metrics. The approach was implemented and tested on a corpus of 6,608 sentences from the International Building Code and its amendments. The sentence clusters and identified sentence types were evaluated using intrinsic and extrinsic evaluation methods. The evaluation results indicated good clustering performance, perfect alignment between the human- and computer-identified types, and good agreement in the assignment of sentences to the types.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request (building-code sentence data and computational code for the clustering-based computability analysis).
Acknowledgments
The authors would like to thank the National Science Foundation (NSF). This material is based on work supported by the NSF under Grant No. 1827733. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the NSF.
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Journal of Computing in Civil Engineering
Volume 35 • Issue 6 • November 2021
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© 2021 American Society of Civil Engineers.
History
Received: Jul 21, 2020
Accepted: Dec 21, 2020
Published online: Aug 23, 2021
Published in print: Nov 1, 2021
Discussion open until: Jan 23, 2022
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