Year: 2016
Type: article
Abstract: Names in programming are vital for understanding the meaning of code and big data. We define code2brain (C2B) interfaces as maps in compilers and brains between meaning and naming syntax, which help to understand executable code. While working toward an Evolvix syntax for general-purpose programming that makes accurate modeling easy for biologists, we observed how names affect C2B quality. To protect learning and coding investments, C2B interfaces require long-term backward compatibility and semantic reproducibility (accurate reproduction of computational meaning from coder-brains to reader-brains by code alone). Semantic reproducibility is often assumed until confusing synonyms degrade modeling in biology to deciphering exercises. We highlight empirical naming priorities from diverse individuals and roles of names in different modes of computing to show how naming easily becomes impossibly difficult. We present the Evolvix BEST (Brief, Explicit, Summarizing, Technical) Names concept for reducing naming priority conflicts, test it on a real challenge by naming subfolders for the Project Organization Stabilizing Tool system, and provide naming questionnaires designed to facilitate C2B debugging by improving names used as keywords in a stabilizing programming language. Our experiences inspired us to develop Evolvix using a flipped programming language design approach with some unexpected features and BEST Names at its core.
DOI: 10.1111/nyas.13192
Authors: Laurence Loewe, Katherine S. Scheuer, Seth A. Keel, Vaibhav Vyas, Ben Liblit, Bret Hanlon, Michael C. Ferris, John Yin, Inês Dutra, Anthony Pietsch, Christine G. Javid, Cecilia L. Moog, Jocelyn Meyer, Jerdon Dresel, Brian McLoone, Sonya Loberger, Arezoo Movaghar, Morgaine Gilchrist‐Scott, Yazeed Sabri, Dave Sescleifer, Ivan Pereda‐Zorrilla, Andrew Zietlow, Rodrigo Smith, Samantha Pietenpol, Jacob Goldfinger, Sarah L. Atzen, Erika Freiberg, Noah P. Waters, Claire Nusbaum, Erik Nolan, Alyssa Hotz, Richard M. Kliman, Ayalew Mentewab, Nathan Fregien, Martha Loewe
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $5,080
Funders: National Science Foundation, U.S. Department of Energy, University of Wisconsin-Madison, National Institutes of Health, Office of Science, U.S. Air Force, National Human Genome Research Institute, National Institute of General Medical Sciences, Division of Biological Infrastructure, Advanced Scientific Computing Research
Awards: G102163711, CAREER: Modeling made easy: Extending systems biology modeling approaches to genetics and ecology, G1428956221, G1514190898, G1855443249, G1941799635, G2287611682, G2369914832, G262962599, G3882439697, G409777406, G498139845, G513797252, G5607048534, G604094063, G6671297155, G6848031779, G6918803902, G708992026, G8642141694, G878601127, G8903918469, G9000078774, G9000129672, G969889393, G993149817
OpenAlex ID: W2560639196