EDBT 2026 Demo / reviewers in the wild / expert
Xujiewen Wang
dblp:52/11077
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2014
—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 |
Program analysis · 91% Operating systems · 9% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Program analysis
dynamic analysis |
0.2 | 1 | 2014 | Make it work, make it right, make it fast: building a platform-neutral whole-system dynamic binary analysis platform · ISSTA 2014 |
Program analysis › binary analysis
dynamic binary analysis |
0.2 | 1 | 2014 | Make it work, make it right, make it fast: building a platform-neutral whole-system dynamic binary analysis platform · ISSTA 2014 |
Program analysis › static analysis
taint analysis |
0.2 | 1 | 2014 | Make it work, make it right, make it fast: building a platform-neutral whole-system dynamic binary analysis platform · ISSTA 2014 |
Operating systems › virtualization
virtual machine introspection |
0.1 | 1 | 2014 | Make it work, make it right, make it fast: building a platform-neutral whole-system dynamic binary analysis platform · ISSTA 2014 |
Methods — techniques the papers use, named apart from their topics
just-in-time virtual machine introspection · 0.2instruction-level tainting · 0.2event-driven programming · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2014 | Make it work, make it right, make it fast: building a platform-neutral whole-system dynamic binary analysis platformabstractDynamic binary analysis is a prevalent and indispensable technique in program analysis. While several dynamic binary analysis tools and frameworks have been proposed, all suffer from one or more of: prohibitive performance degradation, semantic gap between the analysis code and the program being analyzed, architecture/OS specificity, being user-mode only, lacking APIs, etc. We present DECAF, a virtual machine based, multi-target, whole-system dynamic binary analysis framework built on top of QEMU. DECAF provides Just-In-Time Virtual Machine Introspection combined with a novel TCG instruction-level tainting at bit granularity, backed by a plugin based, simple-to-use event driven programming interface. DECAF exercises fine control over the TCG instructions to accomplish on-the-fly optimizations. We present 3 platform-neutral plugins - Instruction Tracer, Keylogger Detector, and API Tracer, to demonstrate the ease of use and effectiveness of DECAF in writing cross-platform and system-wide analysis tools. Implementation of DECAF consists of 9550 lines of C++ code and 10270 lines of C code and we evaluate DECAF using CPU2006 SPEC benchmarks and show average overhead of 605% for system wide tainting and 12% for VMI. Andrew Henderson, Aravind Prakash, Lok-Kwong Yan, Xunchao Hu, Xujiewen Wang, Rundong Zhou, Heng Yin 0001 |
ISSTA | 5 |