Abstract
Laws and regulations impact the design of software systems, as they introduce new requirements and constrain existing ones. The analysis of a software system and the degree to which it complies with applicable laws can be greatly facilitated by models of applicable laws. However, laws are inherently voluminous, often consisting of hundreds of pages of text, and so are their models, consisting of thousands of concepts and relationships. This paper studies the possibility of building models of law semi-automatically by using the NómosT tool. Specifically, we present the NómosT architecture and the process by which a user constructs a model of law semi-automatically, by first annotating the text of a law and then generating from it a model. We then evaluate the performance of the tool relative to building a model of a piece of law manually. In addition, we offer statistics on the quality of the final output that suggest that tool supported generation of models of law reduces substantially human effort without affecting the quality of the output.
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Notes
- 1.
The tool is available at http://www.fastsas.com/.
- 2.
Section 37 has 507 words, 14 sentences, Section 43 has 438 words, 12 sentences, Section 54 has 343 words, 10 sentences and Section 78 has 373 words, 13 sentences.
- 3.
Generated models are available at http://www.fastsas.com/Experiments/Ita.
- 4.
Section 13 has 303 words with 12 sentences, Section 14 has 572 words, 21 sentences, Section 41 has 264 words, 12 sentences and Section 42 has 249 words, 13 sentences.
- 5.
Generated models are available at http://www.fastsas.com/Experiments/Ger.
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Acknowledgment
This research has been partially supported by the ERC advanced grant 267856 ‘Lucretius: Foundations for Software Evolution’.
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Zeni, N., Seid, E.A., Engiel, P., Ingolfo, S., Mylopoulos, J. (2016). Building Large Models of Law with NómosT. In: Comyn-Wattiau, I., Tanaka, K., Song, IY., Yamamoto, S., Saeki, M. (eds) Conceptual Modeling. ER 2016. Lecture Notes in Computer Science(), vol 9974. Springer, Cham. https://doi.org/10.1007/978-3-319-46397-1_18
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