Evolvix BEST Names for semantic reproducibility across code2brain interfaces
- Wisconsin Institute for Discovery, Laboratory of Genetics
- Wisconsin Institute for Discovery
- Departments of Computer Sciences
- Statistics
- Wisconsin Institute for Discovery, Departments of Computer Sciences
- Wisconsin Institute for Discovery, Chemical and Biological Engineering University of Wisconsin‐Madison Madison Wisconsin
- Department of Computer Science University of Porto Porto Portugal
- Department of Biology Cedar Crest College Allentown Pennsylvania
- Department of Biology Spelman College Atlanta Georgia
- College of the Menominee Nation Keshena Wisconsin
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.
- Research Organization:
- Argonne National Laboratory (ANL), Argonne, IL (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC); National Science Foundation (NSF); National Institutes of Health (NIH); NHGRI; NIGMS; University of Wisconsin-Madison; U.S. Air Force
- Grant/Contract Number:
- DE‐AC02‐06CH11357; AC02-06CH11357; T32GM007133; 5T32HG002760; 1R01GM086445‐01; FA9550‐15‐1‐0212; 1149123
- OSTI ID:
- 1334369
- Alternate ID(s):
- OSTI ID: 1341331; OSTI ID: 1625920
- Journal Information:
- Annals of the New York Academy of Sciences, Journal Name: Annals of the New York Academy of Sciences Vol. 1387 Journal Issue: 1; ISSN 0077-8923
- Publisher:
- Wiley-BlackwellCopyright Statement
- Country of Publication:
- United States
- Language:
- English
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