Demo Data from EDBT 2026 / reviewers in the wild / expert
Timothy S. Oberg
dblp:92/1913
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2002
—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% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Compilers and program optimization
register allocation |
0.0 | 1 | 2002 | Fast Copy Coalescing and Live-Range Identification · PLDI 2002 |
Compilers and program optimization › intermediate representation
static single assignment form |
0.0 | 1 | 2002 | Fast Copy Coalescing and Live-Range Identification · PLDI 2002 |
Methods — techniques the papers use, named apart from their topics
interference graph · 0.0graph coloring · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2002 | Fast Copy Coalescing and Live-Range IdentificationabstractThis paper presents a fast new algorithm for modeling and reasoning about interferences for variables in a program without constructing an interference graph. It then describes how to use this information to minimize copy insertion for ϕ-node instantiation during the conversion of the static single assignment (SSA) form into the control-flow graph (CFG), effectively yielding a new, very fast copy coalescing and live-range identification algorithm.This paper proves some properties of the SSA form that enable construction of data structures to compute interference information for variables that are considered for folding. The asymptotic complexity of our SSA-to-CFG conversion algorithm is where-is the number of instructions in the program.Performing copy folding during the SSA-to-CFG conversion eliminates the need for a separate coalescing phase while simplifying the intermediate code. This may make graph-coloring register allocation more practical in just in time (JIT) and other time-critical compilers For example, Sun's Hotspot Server Compiler already employs a graph-coloring register allocator[10].This paper also presents an improvement to the classical interference-graph based coalescing optimization that shows adecrease in memory usage of up to three orders of magnitude and a decrease of a factor of two in compilation time, while providing the exact same results.We present experimental results that demonstrate that our algorithm is almost as precise (within one percent on average) as the improved interference-graph-based coalescing algorithm, while requiring three times less compilation time. Zoran Budimlic, Keith D. Cooper, Timothy J. Harvey, Ken Kennedy, Timothy S. Oberg, Steven W. Reeves |
PLDI | 5 |