Demo Data from VLDB 2026 / reviewers in the wild / expert
Bolei Guo
dblp:13/5633
· DBLP profile ↗
3ranked-venue papers
3as first author
0since 2021 · last 2007
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 3 · 3 first-authorSystems, architecture and hardware · 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 |
Program analysis · 33% Program verification · 33% Program synthesis and code generation · 33% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Program synthesis and code generation
inductive program synthesis |
0.1 | 1 | 2007 | Shape analysis with inductive recursion synthesis · PLDI 2007 |
Program verification › program logic
separation logic |
0.1 | 1 | 2007 | Shape analysis with inductive recursion synthesis · PLDI 2007 |
Program analysis › static analysis › pointer analysis
shape analysis |
0.1 | 1 | 2007 | Shape analysis with inductive recursion synthesis · PLDI 2007 |
Methods — techniques the papers use, named apart from their topics
separation logic · 0.1inductive program synthesis · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2007 | Shape analysis with inductive recursion synthesisabstractSeparation logic with recursively defined predicates allows for concise yet precise description of the shapes of data structures. However, most uses of separation logic for program analysis rely on pre-defined recursive predicates, limiting the class of programs analyzable to those that manipulate only a priori data structures. This paper describes a general algorithm based on inductive program synthesis that automatically infers recursive shape invariants, yielding a shape analysis based on separation logic that can be applied to any program. Bolei Guo, Neil Vachharajani, David I. August |
PLDI | 1 |
| 2006 | Selective Runtime Memory Disambiguation in a Dynamic Binary Translator
Bolei Guo, Youfeng Wu, Cheng Wang 0013, Matthew J. Bridges, Guilherme Ottoni, Neil Vachharajani, David I. August |
CC | 1 |
| 2005 | Practical and Accurate Low-Level Pointer AnalysisabstractPointer analysis is traditionally performed once, early in the compilation process, upon an intermediate representation (IR) with source-code semantics. However, performing pointer analysis only once at this level imposes a phase-ordering constraint, causing alias information to become stale after subsequent code transformations. Moreover, high-level pointer analysis cannot be used at link time or run time, where the source code is unavailable. This paper advocates performing pointer analysis on a low-level intermediate representation. We present the first context-sensitive and partially flow-sensitive points-to analysis designed to operate at the assembly level. As we will demonstrate, low-level pointer analysis can be as accurate as high-level analysis. Additionally, our low-level pointer analysis also enables a quantitative comparison of propagating high-level pointer analysis results through subsequent code transformations, versus recomputing them at the low level. We show that, for C programs, the former practice is considerably less accurate than the latter. Bolei Guo, Matthew J. Bridges, Spyridon Triantafyllis, Guilherme Ottoni, Easwaran Raman, David I. August |
CGO | 1 |