The Community for Technology Leaders
RSS Icon
Subscribe
Issue No.10 - October (1994 vol.20)
pp: 785-797
ABSTRACT
<p>This paper describes some results of what, to the authors' knowledge, is the largest N-version programming experiment ever performed. The object of this ongoing four-year study is to attempt to determine just how consistent the results of scientific computation really are, and, from this, to estimate accuracy. The experiment is being carried out in a branch of the earth sciences known as seismic data processing, where 15 or so independently developed large commercial packages that implement mathematical algorithms from the same or similar published specifications in the same programming language (Fortran) have been developed over the last 20 years. The results of processing the same input dataset, using the same user-specified parameters, for nine of these packages is reported in this paper. Finally, feedback of obvious flaws was attempted to reduce the overall disagreement. The results are deeply disturbing. Whereas scientists like to think that their code is accurate to the precision of the arithmetic used, in this study, numerical disagreement grows at around the rate of 1% in average absolute difference per 4000 fines of implemented code, and, even worse, the nature of the disagreement is nonrandom. Furthermore, the seismic data processing industry has better than average quality standards for its software development with both identifiable quality assurance functions and substantial test datasets.</p>
INDEX TERMS
programming; seismology; geophysics computing; software packages; software quality; scientific software; N-version programming experiment; scientific computation; seismic data processing; large commercial packages; mathematical algorithms; programming language; Fortran; input dataset; seismic data processing industry; quality standards; software development; quality assurance
CITATION
L. Hatton, A. Roberts, "How Accurate is Scientific Software?", IEEE Transactions on Software Engineering, vol.20, no. 10, pp. 785-797, October 1994, doi:10.1109/32.328993
21 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool