Demo Data from VLDB 2026 / reviewers in the wild / expert
Ilaria Tavecchia
dblp:145/4106
· 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 |
Software testing · 50% Software maintenance and evolution · 50% | |
| Network and information security
1 paper |
Network security · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Network security › intrusion detection and prevention › intrusion detection
anomaly detection |
0.2 | 1 | 2014 | Checking app behavior against app descriptions · ICSE 2014 |
Software maintenance and evolution › API usage
API usage analysis |
0.2 | 1 | 2014 | Checking app behavior against app descriptions · ICSE 2014 |
Software testing
mobile application testing |
0.2 | 1 | 2014 | Checking app behavior against app descriptions · ICSE 2014 |
Methods — techniques the papers use, named apart from their topics
outlier detection · 0.4clustering · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2014 | Checking app behavior against app descriptionsabstractHow do we know a program does what it claims to do? After clustering Android apps by their description topics, we identify outliers in each cluster with respect to their API usage. A "weather" app that sends messages thus becomes an anomaly; likewise, a "messaging" app would typically not be expected to access the current location. Applied on a set of 22,500+ Android applications, our CHABADA prototype identified several anomalies; additionally, it flagged 56% of novel malware as such, without requiring any known malware patterns. Alessandra Gorla, Ilaria Tavecchia, Florian Gross, Andreas Zeller |
ICSE | 2 |