Demo Data from EDBT 2026 / reviewers in the wild / expert
Elliot Barlas
dblp:28/6955
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2007
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 1 · 1 first-author
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 verification · 100% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Distributed systems · 100% |
Topics — the 1 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Program verification
distributed system verification |
0.1 | 1 | 2007 | Netstub: a framework for verification of distributed java applications · ASE 2007 |
Methods — techniques the papers use, named apart from their topics
stub classes · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2007 | Netstub: a framework for verification of distributed java applicationsabstractAutomated verification of distributed programs is a challenging problem. Since the behavior of a distributed program encompasses the behavior of the network, possible configurations of the network have to be investigated during verification. This leads to very large state spaces, and automated verification becomes infeasible. We present a framework that addresses this problem by decoupling the behavior of distributed programs from the behavior of the network. Our framework is based on a set of stub classes that replace native methods used in network communication and enables verification of distributed Java applications by isolating their behavior from the network. The framework supports two modes of verification: unit verification and integration verification. Integration verification checks multiple interacting distributed application components by running them in a single JVM and simulating the behavior of the network within the same JVM via stub classes. Unit verification targets a single component of a distributed application and requires that the user write an event generator class that utilizes the API exported by the framework. While unit verification only checks a single application component, it benefits from a greatly reduced state space compared do that of integration verification Elliot Barlas, Tevfik Bultan |
ASE | 1 |