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10 J. Bus. & Tech. L. 297 (2015)
Law Is Code: A Software Engineering Approach to Analyzing the United States Code

handle is hein.journals/jobtela10 and id is 313 raw text is: WILLIAM LI,* PABLO AZAR,** DAVID LAROCHELLE,*** PHIL HILL,**** AND ANDREW W. Lo*****t Law is Code: A Software Engineering Approach to Analyzing the United States Code ABSTRACT The agglomeration of rules and regulations over time has produced a body of legal code that no single individual can fully comprehend. This complexity produces inefficiencies, makes the processes of understanding and changing the law difficult, and frustrates the fundamental principle that the law should provide fair notice to the governed. In this Article, we take a quantitative, unbiased, and software- engineering approach to analyze the evolution of the United States Code from 1926 to today. Software engineers frequently face the challenge of understanding and managing large, structured collections of instructions, directives, and conditional statements, and we adapt and apply their techniques to the U.S. Code over time. Our work produces insights into the structure of the U.S. Code as a whole, its strengths and vulnerabilities, and new ways of thinking about individual laws. For example, we identify the first appearance and spread of important terms in the U.S. © 2015 William Li, Pablo Azar, David Larochelle, Phil Hill, and Andrew W. Lo William Li is a Ph.D. student in the Computer Science and Artificial Intelligence Laboratory (CSAIL) and a 2012 graduate of the Technology and Policy Program at the Massachusetts Institute of Technology (MIT). - Pablo Azar is a doctoral student in Economics at the Massachusetts Institute of Technology (MIT) and a 2014 Computer Science Ph.D. graduate of MIT. David Larochelle is an engineer at the Berkman Center for Internet & Society at Harvard University. * Phil Hill is an associate with Kirkland & Ellis LLP. He is a past Fellow at the Berkman Center for Internet & Society at Harvard University and a 2013 J.D. graduate of Harvard Law School. ***** Andrew W. Lo is the Charles E. and Susan T. Harris Professor at the MIT Sloan School of Management, Principal Investigator in the Computer Science and Artificial Intelligence Laboratory (CSAIL) at the Massachusetts Institute of Technology (MIT), and a joint faculty in the MIT Electrical Engineering and Computer Science Department. t We thank seminar participants at Columbia University, Indiana University, the International Monetary Fund, MIT's Computer Science and Artificial Intelligence Laboratory, Harvard's Berkman Center for Internet & Society, the 2015 New England Database Day conference, the Pacific Institute of Mathematical Sciences, and Yale Law School for helpful comments and discussion. Research support from the MIT Laboratory for Financial Engineering is gratefully acknowledged. We also thank Jayna Cummings, the Journal of Business 6& Technology Law's editor- in-chief, Nicholas R. Rodriguez, and the Journal's editorial board for many helpful editorial comments. JOURNAL OF BUSINESS & TECHNOLOGY LAW

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