Demo Data from EDBT 2026 / reviewers in the wild / expert
Mari A. Aoki
dblp:436/4423
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2026
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 1 · 1 since 2021Theory of computation · 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 |
Requirements engineering and software design · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Requirements engineering and software design
requirements elicitation |
1.0 | 1 | 2026 | Requirements Elicitation, Formalization, and Analysis with FRET: A Tutorial · FM (2) 2026 |
Requirements engineering and software design › formal specification
requirements formalization |
1.0 | 1 | 2026 | Requirements Elicitation, Formalization, and Analysis with FRET: A Tutorial · FM (2) 2026 |
Methods — techniques the papers use, named apart from their topics
test case generation · 1.0realizability checking · 1.0FRETish · 1.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | Requirements Elicitation, Formalization, and Analysis with FRET: A TutorialabstractAbstract Formal methods enable the verification of system behavior against requirements that are expressed as formal, mathematical properties. However, translating the often ambiguous natural language requirements that are typically produced by developers and engineers into precise mathematical specifications remains a significant bottleneck in the formal verification process. NASA’s Formal Requirements Elicitation Tool ( FRET ) is an open source tool that addresses this challenge by bridging the gap between natural language requirements and formal specifications that are suitable for automated verification. FRET enables practitioners to express requirements in FRETish , a structured natural language, that balances intuitive readability with formal rigor. FRET automatically translates these requirements into formal properties that verification tools can directly process. This tutorial paper introduces FRET and guides readers through expressing requirements in FRETish . We present the tool’s key analysis capabilities, including simulation, realizability checking, test-case generation, and automated generation of verification conditions for external formal verification tools. Our goal is to provide a comprehensive guide that helps practitioners, regardless of their formal methods background, to effectively leverage FRET in their verification and validation (V&V) workflows. Anastasia Mavridou, Andreas Katis, Mari A. Aoki, Marie Farrell |
FM (2) | 3 |