Demo Data from SIGIR 2026 / reviewers in the wild / expert
Philip Wickline
dblp:20/5684
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 1998
—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 |
Programming languages and type systems · 39% Runtime systems and virtual machines · 30% Compilers and program optimization · 30% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Programming languages and type systems › type systems
modal type systems |
0.0 | 1 | 1998 | Run-time Code Generation and Modal-ML · PLDI 1998 |
Runtime systems and virtual machines › dynamic compilation
run-time code generation |
0.0 | 1 | 1998 | Run-time Code Generation and Modal-ML · PLDI 1998 |
Compilers and program optimization › program specialization
runtime specialization |
0.0 | 1 | 1998 | Run-time Code Generation and Modal-ML · PLDI 1998 |
Programming languages and type systems › language implementation
abstract machines |
0.0 | 1 | 1998 | Run-time Code Generation and Modal-ML · PLDI 1998 |
Methods — techniques the papers use, named apart from their topics
type-directed compilation · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1998 | Run-time Code Generation and Modal-MLabstractThis paper presents a typed programming language and compiler for run-time code generation. The language, called ML', extends ML with modal operators in the style of the Mini-ML'e language of Davies and Pfenning. ML' allows programmers to use types to specify precisely the stages of computation in a program. The types also guide the compiler in generating target code that exploits the staging information through the use of run-time code generation. The target machine is currently a version of the Categorical Abstract Machine, called the CCAM, which we have extended with facilities for run-time code generation.This approach allows the programmer to express the staging that he wants directly to the compiler. It also provides a typed framework in which to verify the correctness of his staging intentions, and to discuss his staging decisions with other programmers. Finally, it supports in a natural way multiple stages of run-time specialization, so that dynamically generated code can be used in the generation of yet further specialized code.This paper presents an overview of the language, with several examples of programs that illustrate key concepts and programming techniques. Then, it discusses the CCAM and the compilation of ML' programs into CCAM code. Finally, the results of some experiments are shown, to demonstrate the benefits of this style of run-time code generation for some applications. Philip Wickline, Peter Lee 0001, Frank Pfenning |
PLDI | 1 |