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Chris J. Banks

dblp:152/1532 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2014
0000-0001-7650-1598ORCID · reported

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

Theory of computation · 1 · 1 first-author

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.

Theoretical computer science
1 paper
Logic in computer science · 50% Automated reasoning and model checking · 50%
Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

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

TopicWeightPapersLastEvidence papers
Automated reasoning and model checking
model checking
0.212014
A logic of behaviour in context · Inf. Comput. 2014
Logic in computer science
temporal logic
0.212014
A logic of behaviour in context · Inf. Comput. 2014
Bioinformatics and computational biology › systems biology
biochemical system modeling
0.112014
A logic of behaviour in context · Inf. Comput. 2014

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

ordinary differential equation solving · 0.4
YearPublicationVenuePosition
2014 A logic of behaviour in context
abstract
We present a novel temporal logic for expressing properties of behaviour in context . The logic is applied to models of continuous processes, specifically using the continuous π -calculus as a modelling language for biochemical systems. The logic allows the expression of the temporal behaviour of a system when placed in the context of another system. Here we study this in terms of biochemical reactions and the expression of temporal behaviour in the context of other biochemical processes. We present the syntax and semantics of the logic and study the model-checking problem over continuous time and continuous state-space process models, using the continuous π -calculus. We present a succinct, but naive, model-checking algorithm and then show how this can be improved. We investigate the complexity of model-checking, where repeated ODE solving emerges as a particular cost; assess some limitations of the technique; and identify potential routes to overcome these.
Chris J. Banks, Ian Stark
Inf. Comput.1