Demo Data from EDBT 2026 / reviewers in the wild / expert
Anthony DeRossi
dblp:217/9673
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2018
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Human-computer interaction and ubiquitous computing · 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 |
Empirical software engineering · 56% Program verification · 44% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Empirical software engineering
gamification |
0.3 | 1 | 2018 | Inferring Loop Invariants through Gamification · CHI 2018 |
Program verification › invariant generation
loop invariant generation |
0.3 | 1 | 2018 | Inferring Loop Invariants through Gamification · CHI 2018 |
Empirical software engineering
crowdsourcing |
0.1 | 1 | 2018 | Inferring Loop Invariants through Gamification · CHI 2018 |
Methods — techniques the papers use, named apart from their topics
gamification · 0.3crowdsourcing · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2018 | Inferring Loop Invariants through GamificationabstractIn today's modern world, bugs in software systems incur significant costs. One promising approach to improve software quality is automated software verification. In this approach, an automated tool tries to prove the software correct once and for all. Although significant progress has been made in this direction, there are still many cases where automated tools fail. We focus specifically on one aspect of software verification that has been notoriously hard to automate: inferring loop invariants that are strong enough to enable verification. In this paper, we propose a solution to this problem through gamification and crowdsourcing. In particular, we present a puzzle game where players find loop invariants without being aware of it, and without requiring any expertise on software verification. We show through an experiment with Mechanical Turk users that players enjoy the game, and are able to solve verification tasks that automated state-of-the-art tools cannot. Dimitar Bounov, Anthony DeRossi, Massimiliano Menarini, William G. Griswold, Sorin Lerner |
CHI | 2 |