Demo Data from SIGIR 2026 / reviewers in the wild / expert
Paul Wu
dblp:10/5267
· DBLP profile ↗
2ranked-venue papers
2as first author
0since 2021 · last 2008
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 2 · 2 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.
| Databases, data mining, and information retrieval
1 paper |
Transaction processing and concurrency control · 100% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Storage systems · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Transaction processing and concurrency control › concurrency control
locking |
0.1 | 1 | 2008 | The Efficacy of Commutativity-Based Semantic Locking in a Real-World Application · IEEE Trans. Knowl. Data Eng. 2008 |
Transaction processing and concurrency control › concurrency control › locking
object locking |
0.1 | 1 | 2008 | The Efficacy of Commutativity-Based Semantic Locking in a Real-World Application · IEEE Trans. Knowl. Data Eng. 2008 |
Transaction processing and concurrency control › concurrency control › locking
semantic locking |
0.1 | 1 | 2008 | The Efficacy of Commutativity-Based Semantic Locking in a Real-World Application · IEEE Trans. Knowl. Data Eng. 2008 |
Storage systems
object storage |
0.0 | 1 | 2008 | The Efficacy of Commutativity-Based Semantic Locking in a Real-World Application · IEEE Trans. Knowl. Data Eng. 2008 |
Methods — techniques the papers use, named apart from their topics
strict two-phase locking · 0.2commutativity-based semantic locking · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2008 | The Efficacy of Commutativity-Based Semantic Locking in a Real-World ApplicationabstractWhile the dominant approach to persistent storage in practice is to use a relational DBMS, there are some specialist applications that rely on object stores. The performance of these applications depends on the efficiency of the object store's concurrency control mechanism. Today's predominant concurrency control mechanism is strict two-phase object locking. In the 1980s, an interesting alternative was developed: commutativity-based semantic locking. In theory, it can outperform traditional locking schemes in certain scenarios with appropriate commutativity potential. In this paper, we study the real-world performance of different locking strategies in a particular industrial application from the telecommunications sector. We compare object-based locking and commutativity-based semantic locking. We found that, in this application, semantic locking performs equally to, but no better than, object locking in reasonable mixes of real- world transactions, and that it only outperforms in a deliberately contrived mix. Paul Wu, Alan D. Fekete, Uwe Röhm |
IEEE Trans. Knowl. Data Eng. | 1 |
| 2003 | An Empirical Study of Commutativity in Application CodeabstractA typical object database manages concurrency control by instance locking, based on the identification of instance operations as "read" or "write". An alternative theory shows that additional concurrency can be obtained based on operation commutativity. Under commutativity theory, activities can be allowed concurrently as long as they commute, that is, the effect is the same in either order. In this paper, we study an extensive commercial application from a telecommunications domain, and determine how much concurrency is actually present for commutativity theory to use. Our study extends to identify not only the operations that commute, but the reasons for their commutativity as well. We separated the commutative operations into three categories: those that commute because both are read operations, those that commute because different fields are accessed, and those that commute for semantic reasons. By doing this in our analysis we were able to show a comparison in concurrency potential between commutative locking and the two other common locking protocols in existence: instance locking and attribute locking. Paul Wu, Alan D. Fekete |
IDEAS | 1 |