Demo Data from EDBT 2026 / reviewers in the wild / expert
Jerry James
dblp:54/5885
· DBLP profile ↗
6ranked-venue papers
6as first author
0since 2021 · last 2001
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 4 · 4 first-authorTheory of computation · 2 · 2 first-authorDatabases, data management, data science and information retrieval · 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
3 papers |
Distributed computing theory · 100% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Distributed systems · 100% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Distributed computing theory
shared memory consistency |
0.0 | 2 | 1997 | Fault Tolerance Bounds for Memory Consistency · PODC 1997 Complete Implementations for Shared Memory Consistency Conditions (Abstract) · PODC 1995 |
Distributed systems
fault tolerance |
0.0 | 1 | 1999 | External Logging on a Logical Ring · PODC 1999 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2001 | Recovering distributed objects
Jerry James, Ambuj K. Singh |
Inf. Process. Lett. | 1 |
| 2000 | Design of the Kan distributed object systemabstractDistributed software problems are often addressed with object-oriented solutions. Objects provide the benefits of encapsulation and abstraction that have proven useful in managing the complexity of sequential code. However, the management of distributed objects is typically by means of complex APIs, such as CORBA, DCOM, or Java RMI. The complexity of the APIs is itself a hurdle to the writing of efficient, robust programs. An alternate approach is to provide the programmer with a simple interface to an underlying object management layer that provides efficient access to objects and sufficient power for common distributed programming tasks. This paper describes the implementation of the Kan system. It has a clear, simple object model with powerful semantics, embodying such concepts as atomic transactions, asynchronous method calls, and multithreading. The model primitives help the programmer avoid common concurrent programming errors, allowing clean expressions of concurrent algorithms. Kan provides distributed objects (i.e. objects that can migrate or be replicated), rather than the remote objects of Java RMI. Nevertheless, Kan optimizations provide runtime object accesses that are as efficient as or more efficient than accesses made to a similar distribution control layer over Java RMI. We describe the optimizations and measure their runtime impacts. Copyright © 2000 John Wiley & Sons, Ltd. Jerry James, Ambuj K. Singh |
Concurr. Pract. Exp. | 1 |
| 1999 | External Logging on a Logical RingabstractNo abstract available. Jerry James, Ambuj K. Singh |
PODC | 1 |
| 1997 | Fault Tolerance Bounds for Memory ConsistencyabstractNo abstract available. Jerry James, Ambuj K. Singh |
PODC | 1 |
| 1996 | The Impact of Hardware Models on Shared Memory Consistency Conditions
Jerry James, Ambuj K. Singh |
CONCUR | 1 |
| 1995 | Complete Implementations for Shared Memory Consistency Conditions (Abstract)abstractNo abstract available. Jerry James, Ambuj K. Singh |
PODC | 1 |