Demo Data from EDBT 2026 / reviewers in the wild / expert
Shengxin Wu
dblp:426/3336
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2025
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 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.
| Network and information security
1 paper |
Systems and software security · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Systems and software security › memory safety
memory error detection |
0.9 | 1 | 2025 | Protecting Source Code Privacy When Hunting Memory Bugs · ASE 2025 |
Systems and software security › software protection
source code privacy |
0.3 | 1 | 2025 | Protecting Source Code Privacy When Hunting Memory Bugs · ASE 2025 |
Methods — techniques the papers use, named apart from their topics
type minimization · 0.9set cover reduction · 0.9selective pruning · 0.9
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Protecting Source Code Privacy When Hunting Memory BugsabstractWhen proving to a third party that a software system is free from critical memory bugs, software vendors often face the problem of having to reveal their source code, so that the third party can scan the source code using static analysis tools. However, such transparency poses a significant threat to vendors, as the source code typically contains proprietary algorithms, core technical innovations, or trade secrets, exposing them to potential intellectual property risks. In this paper, we present a solution that offers a balance between transparency and code privacy, allowing software vendors to provide minimal source code information while justifying the sufficiency of bug detection. To this end, we propose DIReducer, which reduces source code information, a.k.a. debug information, from non-stripped binaries while preserving its utility for memory bug detection. DIReducer consists of two components: selective pruning and type minimization. The former eliminates redundant debug information, and the latter is proven to be NP-hard and minimizes type-related debug information by reducing it to the classic set-cover problem, which offers a near-optimal solution. Experimental results show that we can reduce 95% of debug information while maintaining similar bug detection capability compared to using full debug information or the source code. Jielun Wu, Bing Shui, Hongcheng Fan, Shengxin Wu, Rongxin Wu, Yang Feng 0003, Baowen Xu, Qingkai Shi |
ASE | 4 |