EDBT 2026 Demo / reviewers in the wild / expert
Trisha Quan
dblp:69/6777
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2008
—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 |
Debugging and program repair · 100% | |
| Theoretical computer science
1 paper |
Logic in computer science · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Debugging and program repair › automated diagnosis
error explanation |
0.1 | 1 | 2008 | Error Reporting Logic · ASE 2008 |
Debugging and program repair
fault localization |
0.1 | 1 | 2008 | Error Reporting Logic · ASE 2008 |
Logic in computer science
first-order logic |
0.0 | 1 | 2008 | Error Reporting Logic · ASE 2008 |
Methods — techniques the papers use, named apart from their topics
user study · 0.2heuristic responsible-object identification · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2008 | Error Reporting LogicabstractWhen a system fails to meet its specification, it can be difficult to find the source of the error and determine how to fix it. In this paper, we introduce error reporting logic (ERL), an algorithm and tool that produces succinct explanations for why a target system violates a specification expressed in first order predicate logic. ERL analyzes the specification to determine which parts contributed to the failure, and it displays an error message specific to those parts. Additionally, ERL uses a heuristic to determine which object in the target system is responsible for the error. Results from a small user study suggest that the combination of a more focused error message and a responsible object for the error helps users to find the failure in the system more effectively. The study also yielded insights into how the users find and fix errors that may guide future research. Ciera Jaspan, Trisha Quan, Jonathan Aldrich |
ASE | 2 |