Demo Data from VLDB 2026 / reviewers in the wild / expert
Mikael Brockman
dblp:382/0995
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2024
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 1 · 1 since 2021Theory of computation · 1 · 1 since 2021
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% Program verification · 50% | |
| Network and information security
1 paper |
Blockchain and cryptocurrency security · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Program verification › equivalence checking
semantic equivalence checking |
0.8 | 1 | 2024 | Hevm, a Fast Symbolic Execution Framework for EVM Bytecode · CAV (1) 2024 |
Program analysis
symbolic execution |
0.8 | 1 | 2024 | Hevm, a Fast Symbolic Execution Framework for EVM Bytecode · CAV (1) 2024 |
Blockchain and cryptocurrency security › smart contract analysis
smart contract verification |
0.2 | 1 | 2024 | Hevm, a Fast Symbolic Execution Framework for EVM Bytecode · CAV (1) 2024 |
Methods — techniques the papers use, named apart from their topics
symbolic execution · 1.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Hevm, a Fast Symbolic Execution Framework for EVM BytecodeabstractAbstract We present , a symbolic execution engine for the EVM. can prove safety properties for EVM bytecode or verify semantic equivalence between two bytecode objects. It exposes a user-friendly API in Solidity that allows end-users to define symbolic tests using almost the same syntax as they would for their usual unit tests. We evaluate our framework against state-of-the-art tools, using a comprehensive set of benchmarks. Our empirical findings demonstrate that outperforms its counterparts, effectively solving a greater number of problems within competitive time frames. Dxo, Mate Soos, Zoe Paraskevopoulou, Martin Lundfall, Mikael Brockman |
CAV (1) | 5 |