Demo Data from EDBT 2026 / reviewers in the wild / expert
Zeno Montolli
dblp:385/8167
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2024
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 1 · 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.
| Software engineering, system software, and programming languages
1 paper |
Software testing · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Software testing › API testing
REST API testing |
0.8 | 1 | 2024 | DeepREST: Automated Test Case Generation for REST APIs Exploiting Deep Reinforcement Learning · ASE 2024 |
Software testing
test generation |
0.8 | 1 | 2024 | DeepREST: Automated Test Case Generation for REST APIs Exploiting Deep Reinforcement Learning · ASE 2024 |
Software testing
black-box testing |
0.2 | 1 | 2024 | DeepREST: Automated Test Case Generation for REST APIs Exploiting Deep Reinforcement Learning · ASE 2024 |
Software testing
specification-based testing |
0.2 | 1 | 2024 | DeepREST: Automated Test Case Generation for REST APIs Exploiting Deep Reinforcement Learning · ASE 2024 |
Methods — techniques the papers use, named apart from their topics
deep reinforcement learning · 0.8OpenAPI Specification · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | DeepREST: Automated Test Case Generation for REST APIs Exploiting Deep Reinforcement LearningabstractAutomatically crafting test scenarios for REST APIs helps deliver more reliable and trustworthy web-oriented systems. However, current black-box testing approaches rely heavily on the information available in the API's formal documentation, i.e., the Open API Specification (OAS for short). While useful, the OAS mostly covers syntactic aspects of the API (e.g., producer-consumer relations between operations, input value properties, and additional constraints in natural language), and it lacks a deeper understanding of the API business logic. Missing semantics include implicit ordering (logic dependency) between operations and implicit input-value constraints. These limitations hinder the ability of black-box testing tools to generate truly effective test cases automatically. Davide Corradini, Zeno Montolli, Michele Pasqua, Mariano Ceccato |
ASE | 2 |