Demo Data from EDBT 2026 / reviewers in the wild / expert
Jake Silverman
dblp:183/9781
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2019
—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-authorTheory of computation · 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 analysis · 100% | |
| Theoretical computer science
1 paper |
Automated reasoning and model checking · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Program analysis › loop analysis
loop summarization |
0.4 | 1 | 2019 | Loop Summarization with Rational Vector Addition Systems · CAV (2) 2019 |
Program analysis
static analysis |
0.4 | 1 | 2019 | Loop Summarization with Rational Vector Addition Systems · CAV (2) 2019 |
Automated reasoning and model checking › invariant generation
loop invariant generation |
0.4 | 1 | 2019 | Loop Summarization with Rational Vector Addition Systems · CAV (2) 2019 |
Automated reasoning and model checking
program verification |
0.4 | 1 | 2019 | Loop Summarization with Rational Vector Addition Systems · CAV (2) 2019 |
Methods — techniques the papers use, named apart from their topics
reachability analysis · 0.8abstract interpretation · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | Loop Summarization with Rational Vector Addition SystemsabstractThis paper presents a technique for computing numerical loop summaries. The method synthesizes a rational vector addition system with resets ( $$\mathbb {Q}$$ -VASR) that simulates the action of an input loop, and then uses the reachability relation of that $$\mathbb {Q}$$ -VASR to over-approximate the behavior of the loop. The key technical problem solved in this paper is to automatically synthesize a $$\mathbb {Q}$$ -VASR that is a best abstraction of a given loop in the sense that (1) it simulates the loop and (2) it is simulated by any other $$\mathbb {Q}$$ -VASR that simulates the loop. Since our loop summarization scheme is based on computing the exact reachability relation of a best abstraction of a loop, we can make theoretical guarantees about its behavior. Moreover, we show experimentally that the technique is precise and performant in practice. Jake Silverman, Zachary Kincaid |
CAV (2) | 1 |