Demo Data from SIGIR 2026 / reviewers in the wild / expert
Antoine Moynault
dblp:235/2491
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2019
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 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 |
Program analysis · 50% Compilers and program optimization · 50% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Program analysis
dynamic analysis |
0.4 | 1 | 2019 | Data-flow/dependence profiling for structured transformations · PPoPP 2019 |
Compilers and program optimization › dynamic optimization
profile-guided optimization |
0.4 | 1 | 2019 | Data-flow/dependence profiling for structured transformations · PPoPP 2019 |
Methods — techniques the papers use, named apart from their topics
profiling · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | Data-flow/dependence profiling for structured transformationsabstractProfiling feedback is an important technique used by developers for performance debugging, where it is usually used to pinpoint performance bottlenecks and also to find optimization opportunities. Assessing the validity and potential benefit of a program transformation requires accurate knowledge of the data flow and dependencies, which can be uncovered by profiling a particular execution of the program. Fabian Gruber, Manuel Selva, Diogo Sampaio, Christophe Guillon, Antoine Moynault, Louis-Noël Pouchet, Fabrice Rastello |
PPoPP | 5 |