Dataset Information

Evolvix BEST Names for semantic reproducibility across code2brain interfaces.

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.

SUBMITTER: Loewe L

PROVIDER: S-EPMC5299481 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature

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Evolvix BEST Names for semantic reproducibility across code2brain interfaces.

Loewe Laurence L Scheuer Katherine S KS Keel Seth A SA Vyas Vaibhav V Liblit Ben B Hanlon Bret B Ferris Michael C MC Yin John J Dutra Inês I Pietsch Anthony A Javid Christine G CG Moog Cecilia L CL Meyer Jocelyn J Dresel Jerdon J McLoone Brian B Loberger Sonya S Movaghar Arezoo A Gilchrist-Scott Morgaine M Sabri Yazeed Y Sescleifer Dave D Pereda-Zorrilla Ivan I Zietlow Andrew A Smith Rodrigo R Pietenpol Samantha S Goldfinger Jacob J Atzen Sarah L SL Freiberg Erika E Waters Noah P NP Nusbaum Claire C Nolan Erik E Hotz Alyssa A Kliman Richard M RM Mentewab Ayalew A Fregien Nathan N Loewe Martha M

Annals of the New York Academy of Sciences 20161205 1

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 sem ...[more]

PMID: 27918836

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Project description:BackgroundConfusion between look-alike and sound-alike (LASA) medication names (such as mercaptamine and mercaptopurine) accounts for up to one in four medication errors, threatening patient safety. Error reduction strategies include computerized physician order entry interventions, and 'Tall Man' lettering. The purpose of this study is to explore the medication name designation process, to elucidate properties that may prime the risk of confusion.Methods and findingsWe analysed the formal and semantic properties of 7,987 International Non-proprietary Names (INNs), in relation to naming guidelines of the World Health Organization (WHO) INN programme, and have identified potential for errors. We explored: their linguistic properties, the underlying taxonomy of stems to indicate pharmacological interrelationships, and similarities between INNs. We used Microsoft Excel for analysis, including calculation of Levenshtein edit distance (LED). Compliance with WHO naming guidelines was inconsistent. Since the 1970s there has been a trend towards compliance in formal properties, such as word length, but longer names published in the 1950s and 1960s are still in use. The stems used to show pharmacological interrelationships are not spelled consistently and the guidelines do not impose an unequivocal order on them, making the meanings of INNs difficult to understand. Pairs of INNs sharing a stem (appropriately or not) often have high levels of similarity (<5 LED), and thus have greater potential for confusion.ConclusionsWe have revealed a tension between WHO guidelines stipulating use of stems to denote meaning, and the aim of reducing similarities in nomenclature. To mitigate this tension and reduce the risk of confusion, the stem system should be made clear and well ordered, so as to avoid compounding the risk of confusion at the clinical level. The interplay between the different WHO INN naming principles should be further examined, to better understand their implications for the problem of LASA errors.

Dataset Information

Evolvix BEST Names for semantic reproducibility across code2brain interfaces.

Publications

Evolvix BEST Names for semantic reproducibility across code2brain interfaces.

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