VLDB 2026 Research / reviewers in the wild / expert
Rick Reitmaier
dblp:57/4267
· DBLP profile ↗
2ranked-venue papers
0as first author
0since 2021 · last 2009
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 1Software 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 |
Runtime systems and virtual machines · 61% Compilers and program optimization · 30% Programming languages and type systems · 9% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Runtime systems and virtual machines › dynamic compilation
just-in-time compilation |
0.1 | 1 | 2009 | Trace-based just-in-time type specialization for dynamic languages · PLDI 2009 |
Runtime systems and virtual machines › dynamic compilation › just-in-time compilation
trace-based compilation |
0.1 | 1 | 2009 | Trace-based just-in-time type specialization for dynamic languages · PLDI 2009 |
Compilers and program optimization › program specialization
type specialization |
0.1 | 1 | 2009 | Trace-based just-in-time type specialization for dynamic languages · PLDI 2009 |
Programming languages and type systems
dynamic languages |
0.0 | 1 | 2009 | Trace-based just-in-time type specialization for dynamic languages · PLDI 2009 |
Methods — techniques the papers use, named apart from their topics
type specialization · 0.1trace compilation · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2009 | Trace-based just-in-time type specialization for dynamic languagesabstractDynamic languages such as JavaScript are more difficult to compile than statically typed ones. Since no concrete type information is available, traditional compilers need to emit generic code that can handle all possible type combinations at runtime. We present an alternative compilation technique for dynamically-typed languages that identifies frequently executed loop traces at run-time and then generates machine code on the fly that is specialized for the actual dynamic types occurring on each path through the loop. Our method provides cheap inter-procedural type specialization, and an elegant and efficient way of incrementally compiling lazily discovered alternative paths through nested loops. We have implemented a dynamic compiler for JavaScript based on our technique and we have measured speedups of 10x and more for certain benchmark programs. Andreas Gal, Brendan Eich, Mike Shaver, David Mandelin, Mohammad R. Haghighat, Blake Kaplan, Graydon Hoare, Boris Zbarsky, Jason Orendorff, Jesse Ruderman, Edwin W. Smith, Rick Reitmaier, Michael Bebenita, Mason Chang, Michael Franz |
PLDI | 13 |
| 2009 | Tracing for web 3.0: trace compilation for the next generation web applicationsabstractToday's web applications are pushing the limits of modern web browsers. The emergence of the browser as the platform of choice for rich client-side applications has shifted the use of in-browser JavaScript from small scripting programs to large computationally intensive application logic. For many web applications, JavaScript performance has become one of the bottlenecks preventing the development of even more interactive client side applications. While traditional just-in-time compilation is successful for statically typed virtual machine based languages like Java, compiling JavaScript turns out to be a challenging task. Many JavaScript programs and scripts are short-lived, and users expect a responsive browser during page loading. This leaves little time for compilation of JavaScript to generate machine code.We present a trace-based just-in-time compiler for JavaScript that uses run-time profiling to identify frequently executed code paths, which are compiled to executable machine code. Our approach increases execution performance by up to 116% by decomposing complex JavaScript instructions into a simple Forth-based representation, and then recording the actually executed code path through this low-level IR. Giving developers more computational horsepower enables a new generation of innovative web applications. Mason Chang, Edwin W. Smith, Rick Reitmaier, Michael Bebenita, Andreas Gal, Christian Wimmer, Brendan Eich, Michael Franz |
VEE | 3 |