EDBT 2026 Demo / reviewers in the wild / expert
Bruno Castro
dblp:187/1995
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2019
0000-0002-4450-6906ORCID · 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 |
Software maintenance and evolution · 100% |
Topics — the 1 heaviest of 1, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Software maintenance and evolution
feature location |
0.4 | 1 | 2019 | Pangolin: An SFL-Based Toolset for Feature Localization · ASE 2019 |
Methods — techniques the papers use, named apart from their topics
spectrum-based fault localization · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | Pangolin: An SFL-Based Toolset for Feature LocalizationabstractPinpointing the location where a given unit of functionality-or feature-was implemented is a demanding and time-consuming task, yet prevalent in most software maintenance or evolution efforts. To that extent, we present PANGOLIN, an Eclipse plugin that helps developers identifying features among the source code. It borrows Spectrum-based Fault Localization techniques from the software diagnosis research field by framing feature localization as a diagnostic problem. PANGOLIN prompts users to label system executions based on feature involvement, and subsequently presents its spectrum-based feature localization analysis to users with the aid of a color-coded, hierarchic, and navigable visualization which was shown to be effective at conveying diagnostic information to users. Our evaluation shows that PANGOLIN accurately pinpoints feature implementations and is resilient to misclassifications by users. The tool can be downloaded at https://tqrg.github.io/pangolin/. Bruno Castro, Alexandre Perez, Rui Abreu 0001 |
ASE | 1 |