Demo Data from EDBT 2026 / reviewers in the wild / expert
Leonidas Triantafyllou
dblp:269/8191
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2020
—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 · 77% Programming languages and type systems · 23% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Program analysis
static analysis |
0.4 | 1 | 2020 | Identifying Java calls in native code via binary scanning · ISSTA 2020 |
Programming languages and type systems › language implementation › foreign function interface
java native interface |
0.1 | 1 | 2020 | Identifying Java calls in native code via binary scanning · ISSTA 2020 |
Methods — techniques the papers use, named apart from their topics
disassembly · 0.4binary scanning · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2020 | Identifying Java calls in native code via binary scanningabstractCurrent Java static analyzers, operating either on the source or bytecode level, exhibit unsoundness for programs that contain native code. We show that the Java Native Interface (JNI) specification, which is used by Java programs to interoperate with Java code, is principled enough to permit static reasoning about the effects of native code on program execution when it comes to call-backs. Our approach consists of disassembling native binaries, recovering static symbol information that corresponds to Java method signatures, and producing a model for statically exercising these native call-backs with appropriate mock objects. The approach manages to recover virtually all Java calls in native code, for both Android and Java desktop applications—(a) achieving 100% native-to-application call-graph recall on large Android applications (Chrome, Instagram) and (b) capturing the full native call-back behavior of the XCorpus suite programs. Georgios Fourtounis 0001, Leonidas Triantafyllou, Yannis Smaragdakis |
ISSTA | 2 |