Demo Data from EDBT 2026 / reviewers in the wild / expert
Eric F. Rizzi
dblp:142/6150
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2016
0009-0003-6687-8959ORCID · reported
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 |
Empirical software engineering · 77% Program analysis · 23% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Empirical software engineering › software evaluation
tool evaluation |
0.2 | 1 | 2016 | On the techniques we create, the tools we build, and their misalignments: a study of KLEE · ICSE 2016 |
Program analysis
symbolic execution |
0.1 | 1 | 2016 | On the techniques we create, the tools we build, and their misalignments: a study of KLEE · ICSE 2016 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2016 | On the techniques we create, the tools we build, and their misalignments: a study of KLEEabstractOur community constantly pushes the state-of-the-art by introducing "new" techniques. These techniques often build on top of, and are compared against, existing systems that realize previously published techniques. The underlying assumption is that existing systems correctly represent the techniques they implement. This paper examines that assumption through a study of KLEE, a popular and well-cited tool in our community. We briefly describe six improvements we made to KLEE, none of which can be considered "new" techniques, that provide order-of-magnitude performance gains. Given these improvements, we then investigate how the results and conclusions of a sample of papers that cite KLEE are affected. Our findings indicate that the strong emphasis on introducing "new" techniques may lead to wasted effort, missed opportunities for progress, an accretion of artifact complexity, and questionable research conclusions (in our study, 27% of the papers that depend on KLEE can be questioned). We conclude by revisiting initiatives that may help to realign the incentives to better support the foundations on which we build. Eric F. Rizzi, Sebastian G. Elbaum, Matthew B. Dwyer |
ICSE | 1 |