J
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
Thomas Kunz,James P. Black +1 more
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
Thomas Kunz,James P. Black +1 more
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.