Demo Data from EDBT 2026 / reviewers in the wild / expert
Monali Pande
dblp:256/6221
· DBLP profile ↗
1ranked-venue papers
0as 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
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 · 44% Program analysis · 44% Concurrent programming · 13% | |
| Computer graphics and multimedia
1 paper |
Visualization and visual analytics · 100% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Debugging and program repair
fault localization |
0.4 | 1 | 2019 | Visual Analytics for Concurrent Java Executions · ASE 2019 |
Program analysis › dynamic analysis › trace analysis
trace visualization |
0.4 | 1 | 2019 | Visual Analytics for Concurrent Java Executions · ASE 2019 |
Concurrent programming
concurrency bugs |
0.1 | 1 | 2019 | Visual Analytics for Concurrent Java Executions · ASE 2019 |
Methods — techniques the papers use, named apart from their topics
zooming · 0.8trace filtering · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | Visual Analytics for Concurrent Java ExecutionsabstractAnalyzing executions of concurrent software is very difficult. Even if a trace is available, such traces are very hard to read and interpret. A textual trace contains a lot of data, most of which is not relevant to the issue at hand. Past visualization attempts either do not show concurrent behavior, or result in a view that is overwhelming for the user. We provide a visual analytics tool, VA4JVM, for error traces produced by either the Java Virtual Machine, or by Java Pathfinder. Its key features are a layout that spatially associates events with threads, a zoom function, and the ability to filter event data in various ways. We show in examples how filtering and zooming in can highlight a problem without having to read lengthy textual data. Cyrille Artho, Monali Pande, Qiyi Tang 0001 |
ASE | 2 |