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Yuichiro Oyabu

dblp:220/5703 · DBLP profile ↗
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3ranked-venue papers
0as first author
2since 2021 · last 2024
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 3 · 2 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
Program analysis · 50% Program verification · 50%
Theoretical computer science
1 paper
Logic in computer science · 100%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Program analysis › static analysis
probabilistic program analysis
0.512021
Ranking and Repulsing Supermartingales for Reachability in Randomized Programs · ACM Trans. Program. Lang. Syst. 2021
Logic in computer science › domain theory
fixed points
0.512021
Ranking and Repulsing Supermartingales for Reachability in Randomized Programs · ACM Trans. Program. Lang. Syst. 2021

Methods — techniques the papers use, named apart from their topics

template-based synthesis · 1.0experimental comparison · 1.0
YearPublicationVenuePosition
2024 Control-data separation and logical condition propagation for efficient inference on probabilistic programs
Ichiro Hasuo, Yuichiro Oyabu, Clovis Eberhart, Kohei Suenaga, Kenta Cho 0002, Shin-ya Katsumata
J. Log. Algebraic Methods Program.2
2021 Ranking and Repulsing Supermartingales for Reachability in Randomized Programs
abstract
Computing reachability probabilities is a fundamental problem in the analysis of randomized programs. This article aims at a comprehensive and comparative account of various martingale-based methods for over- and under-approximating reachability probabilities. Based on the existing works that stretch across different communities (formal verification, control theory, etc.), we offer a unifying account. In particular, we emphasize the role of order-theoretic fixed points—a classic topic in computer science—in the analysis of randomized programs. This leads us to two new martingale-based techniques, too. We also make an experimental comparison using our implementation of template-based synthesis algorithms for those martingales.
Toru Takisaka, Yuichiro Oyabu, Natsuki Urabe, Ichiro Hasuo
ACM Trans. Program. Lang. Syst.2
2018 Ranking and Repulsing Supermartingales for Reachability in Probabilistic Programs
Toru Takisaka, Yuichiro Oyabu, Natsuki Urabe, Ichiro Hasuo
ATVA2