Encoding Transparency: Literate Programming and Test Generation for Scientific Function Libraries

16 Pages Posted: 24 Jul 2012  

Mark D. Flood

Government of the United States of America - Office of Financial Research

Matthew McCormick

Government of the United States of America - Office of Financial Research

Nathan M. Palmer

George Mason University - Department of Computational Social Science

Date Written: July 19, 2012

Abstract

We present a variation on literate programming (see Knuth: 1984, 1992) targeting multiple simultaneous readerships, both human (e.g., coders, testers, analysts, etc.) and compilers/interpreters (e.g., C , Python, Fortran, etc.). The technique exploits existing commenting syntax available in all common programming languages to provide inline documentation and other semantic markup, which can then be used in test generation and code translation. To keep the problem manageable, we restrict attention to scientific function libraries (i.e., libraries of numerical routines adhering to the functional programming rule of “no side effects”). We offer a prototype implementation in XSLT and DocBook.

Suggested Citation

Flood, Mark D. and McCormick, Matthew and Palmer, Nathan M., Encoding Transparency: Literate Programming and Test Generation for Scientific Function Libraries (July 19, 2012). Available at SSRN: https://ssrn.com/abstract=2113535 or http://dx.doi.org/10.2139/ssrn.2113535

Mark D. Flood (Contact Author)

Government of the United States of America - Office of Financial Research ( email )

717 14th Street, NW
Washington DC, DC 20005
United States

Matthew McCormick

Government of the United States of America - Office of Financial Research ( email )

717 14th Street, NW
Washington DC, DC 20005
United States

Nathan M. Palmer

George Mason University - Department of Computational Social Science ( email )

4400 University Drive
Research I, CSC Suite, Level 3
Fairfax, VA 22030
United States

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