Demo Data from EDBT 2026 / reviewers in the wild / expert
Juan M. Tamayo
dblp:120/2049
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2012
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 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.
| Software engineering, system software, and programming languages
1 paper |
Program analysis · 100% | |
| Databases, data mining, and information retrieval
1 paper |
Query processing and optimization · 100% |
Topics — the 2 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Program analysis › static analysis
dependency analysis |
0.1 | 1 | 2012 | Understanding the behavior of database operations under program control · OOPSLA 2012 |
Program analysis
static analysis |
0.1 | 1 | 2012 | Understanding the behavior of database operations under program control · OOPSLA 2012 |
Methods — techniques the papers use, named apart from their topics
information flow analysis · 0.3commutativity analysis · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2012 | Understanding the behavior of database operations under program controlabstractApplications that combine general program logic with persistent databases (e.g., three-tier applications) often suffer large performance penalties from poor use of the database. We introduce a program analysis technique that combines information flow in the program with commutativity analysis of its database operations to produce a unified dependency graph for database statements, which provides programmers with a high-level view of how costly database operations are and how they are connected in the program. As an example application of our analysis we describe three optimizations that can be discovered by examining the structure of the dependency graph; each helps remove communication latency from the critical path of a multi-tier system. We implement our technique in a tool for Java applications using JDBC and experimentally validate it using the multi-tier component of the Dacapo benchmark. Juan M. Tamayo, Alex Aiken, Nathan Bronson, Shmuel Sagiv |
OOPSLA | 1 |