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James P. Black

Researcher at University of Waterloo

Publications -  34
Citations -  620

James P. Black is an academic researcher from University of Waterloo. The author has contributed to research in topics: Debugging & Event (computing). The author has an hindex of 11, co-authored 34 publications receiving 591 citations. Previous affiliations of James P. Black include Newcastle University.

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Journal ArticleDOI

Redundancy in Data Structures: Improving Software Fault Tolerance

TL;DR: The intuitive approach of this paper, which makes heavy use of examples, is complemented by the more formal development of the companion paper, "Redundancy in Data Structures: Some Theoretical Results."
Proceedings Article

Minimal sufficient explanations for factored Markov Decision Processes

TL;DR: A technique to explain policies for factored MDP by populating a set of domain-independent templates and a mechanism to determine a minimal set of templates that, viewed together, completely justify the policy.

An architecture for adaptive mobile applications

TL;DR: The components of a flexible and general-purpose runtime infrastructure to facilitate the rapid development and deployment of adaptive mobile applications that adapt dynamically and transparently to the amount of resources available at runtime are developed.
Journal ArticleDOI

POET: Target-system-independent visualizations of complex distributed-application executions

TL;DR: Poet, a tool for the collection and presentation of event-based traces of distributed executions, makes as few assumptions as possible about characteristics that must be possessed by all target environments, revealing that this target-system independence does not impose a performance penalty.
Journal ArticleDOI

Using automatic process clustering for design recovery and distributed debugging

TL;DR: Two approaches to automatic process clustering are discussed, one analyzing runtime information with a statistical approach and one utilizing additional semantic information, indicating that theAdditional semantic information improves the cluster hierarchies derived.