Demo Data from EDBT 2026 / reviewers in the wild / expert
Kevin Frei
dblp:03/5283
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 1997
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 1
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 |
Compilers and program optimization · 100% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Distributed systems · 100% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Compilers and program optimization
code generation |
0.0 | 1 | 1997 | Flick: A Flexible, Optimizing IDL Compiler · PLDI 1997 |
Compilers and program optimization › code generation
stub generation |
0.0 | 1 | 1997 | Flick: A Flexible, Optimizing IDL Compiler · PLDI 1997 |
Distributed systems
remote procedure call |
0.0 | 1 | 1997 | Flick: A Flexible, Optimizing IDL Compiler · PLDI 1997 |
Methods — techniques the papers use, named apart from their topics
marshaling optimization · 0.0intermediate representation · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1997 | Flick: A Flexible, Optimizing IDL CompilerabstractAn interface definition language (IDL) is a nontraditional language for describing interfaces between software components. IDL compilers generate "stubs" that provide separate communicating processes with the abstraction of local object invocation or procedure call. High-quality stub generation is essential for applications to benefit from component-based designs, whether the components reside on a single computer or on multiple networked hosts. Typical IDL compilers, however, do little code optimization, incorrectly assuming that interprocess communication is always the primary bottleneck. More generally, typical IDL compilers are "rigid" and limited to supporting only a single IDL, a fixed mapping onto a target language, and a narrow range of data encodings and transport mechanisms.Flick, our new IDL compiler, is based on the insight that IDLs are true languages amenable to modern compilation techniques. Flick exploits concepts from traditional programming language compilers to bring both flexibility and optimization to the domain of IDL compilation. Through the use of carefully chosen intermediate representations, Flick supports multiple IDLs, diverse data encodings, multiple transport mechanisms, and applies numerous optimizations to all of the code it generates. Our experiments show that Flick-generated stubs marshal data between 2 and 17 times faster than stubs produced by traditional IDL compilers, and on today's generic operating systems, increase end-to-end throughput by factors between 1.2 and 3.7. Eric Eide, Kevin Frei, Bryan Ford, Jay Lepreau, Gary Lindstrom |
PLDI | 2 |