TY  - JOUR
A1  - Coupette, Corinna
A1  - Hartung, Dirk
A1  - Beckedorf, Janis
A1  - Böther, Maximilian
A1  - Katz, Daniel Martin
T1  - Law smells
BT  - defining and detecting problematic patterns in legal drafting
JF  - Artificial intelligence and law
N2  - Building on the computer science concept of code smells, we initiate the study of law smells, i.e., patterns in legal texts that pose threats to the comprehensibility and maintainability of the law. With five intuitive law smells as running examples-namely, duplicated phrase, long element, large reference tree, ambiguous syntax, and natural language obsession-, we develop a comprehensive law smell taxonomy. This taxonomy classifies law smells by when they can be detected, which aspects of law they relate to, and how they can be discovered. We introduce text-based and graph-based methods to identify instances of law smells, confirming their utility in practice using the United States Code as a test case. Our work demonstrates how ideas from software engineering can be leveraged to assess and improve the quality of legal code, thus drawing attention to an understudied area in the intersection of law and computer science and highlighting the potential of computational legal drafting.
KW  - Refactoring
KW  - Software engineering
KW  - Law
KW  - Natural language processing
KW  - Network analysis
Y1  - 2022
U6  - https://doi.org/10.1007/s10506-022-09315-w
SN  - 0924-8463
SN  - 1572-8382
VL  - 31
SP  - 335
EP  - 368
PB  - Springer
CY  - Dordrecht
ER  -