EDBT 2026 Demo / reviewers in the wild / expert
Hima Mynampaty
dblp:431/6376
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2026
0009-0002-6156-7660ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Human-computer interaction and ubiquitous computing · 1 · 1 first-author · 1 since 2021
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.
| Human-computer interaction and pervasive computing
1 paper |
Design research and methods · 100% | |
| Software engineering, system software, and programming languages
1 paper |
Software maintenance and evolution · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Design research and methods
design probe |
1.0 | 1 | 2026 | Linting Style and Substance in READMEs · CHI 2026 |
Software maintenance and evolution › software documentation
documentation quality |
1.0 | 1 | 2026 | Linting Style and Substance in READMEs · CHI 2026 |
Methods — techniques the papers use, named apart from their topics
large language model · 2.0domain-specific language · 2.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | Linting Style and Substance in READMEsabstractREADMEs shape first impressions of software projects, yet what constitutes a good README varies across audiences and contexts. Research software needs reproducibility details, while open-source libraries might prioritize quick-start guides. Through a design probe, LintMe, we explore how linting can be used to improve READMEs given these diverse contexts, aiding style and content issues while preserving authorial agency. Users create context-specific checks using a lightweight DSL that uses a novel combination of programmatic operations (e.g., for broken links) with LLM-based content evaluation (e.g., for detecting jargon), yielding checks that would be challenging for prior linters. Through a user study (N=11), comparison with naive LLM usage, and an extensibility case study, we find that our design is approachable, flexible, and well matched with the needs of this domain. This work opens the door for linting more complex documentation and other culturally mediated text-based documents. Hima Mynampaty, Nathania Josephine, Katherine E. Isaacs, Andrew M. McNutt |
CHI | 1 |