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Andy Roberts

dblp:86/70 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2011
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 2Theory of computation · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%
Theoretical computer science
1 paper
Automated reasoning and model checking · 100%
Software engineering, system software, and programming languages
1 paper
Empirical software engineering · 50% Operating systems · 50%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › systems biology
computational systems biology
0.112011
Synthesizing Biological Theories · CAV 2011
Automated reasoning and model checking
synthesis
0.012011
Synthesizing Biological Theories · CAV 2011
Operating systems › fault tolerance
n-version programming
0.011994
How Accurate Is Scientific Software? · IEEE Trans. Software Eng. 1994

Methods — techniques the papers use, named apart from their topics

statistical analysis · 0.0n-version programming experiment · 0.0
YearPublicationVenuePosition
2011 Synthesizing Biological Theories
Hillel Kugler, Cory Plock, Andy Roberts
CAV3
1994 How Accurate Is Scientific Software?
abstract
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.>
Les Hatton, Andy Roberts
IEEE Trans. Software Eng.2