Yutaka Nagashima

dblp:21/607 · DBLP profile ↗
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10ranked-venue papers
7as first author
1since 2021 · last 2021
0000-0001-6693-5325ORCID · corroborated

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

Software engineering, systems software and programming languages · 7 · 5 first-authorTheory of computation · 5 · 4 first-authorArtificial intelligence and machine learning · 4 · 4 first-author · 1 since 2021Systems, architecture and hardware · 1Graphics, computer vision, multimedia, augmented reality and games · 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.

Theoretical computer science
2 papers
Automated reasoning and model checking · 100%
Software engineering, system software, and programming languages
1 paper
Operating systems · 50% Compilers and program optimization · 50%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Storage systems · 100%

Topics — the 4 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Automated reasoning and model checking › theorem proving
interactive theorem proving
0.822021
Faster Smarter Proof by Induction in Isabelle/HOL · IJCAI 2021
PaMpeR: proof method recommendation system for Isabelle/HOL · ASE 2018
Automated reasoning and model checking
inductive proof
0.512021
Faster Smarter Proof by Induction in Isabelle/HOL · IJCAI 2021
Operating systems › resource management › storage management › file systems
file system verification
0.212016
CoGENT: Verifying High-Assurance File System Implementations · ASPLOS 2016
Compilers and program optimization
verified compilation
0.212016
CoGENT: Verifying High-Assurance File System Implementations · ASPLOS 2016

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

heuristic selection · 0.5formal specification · 0.5dependent types · 0.5certifying compiler · 0.5proof corpus mining · 0.3machine learning · 0.3
YearPublicationVenuePosition
2021 Faster Smarter Proof by Induction in Isabelle/HOL
abstract
We present sem_ind, a recommendation tool for proof by induction in Isabelle/HOL. Given an inductive problem, sem_ind produces candidate arguments for proof by induction, and selects promising ones using heuristics. Our evaluation based on 1,095 inductive problems from 22 source files shows that sem_ind improves the accuracy of recommendation from 20.1% to 38.2% for the most promising candidates within 5.0 seconds of timeout compared to its predecessor while decreasing the median value of execution time from 2.79 seconds to 1.06 seconds.
Yutaka Nagashima
IJCAI1
2020 Smart Induction for Isabelle/HOL (Tool Paper)
abstract
Proof assistants offer tactics to facilitate inductive proofs; however, deciding what arguments to pass to these tactics still requires human ingenuity.To automate this process, we present smart_induct for Isabelle/HOL.Given an inductive problem in any problem domain, smart_induct lists promising arguments for the induct tactic without relying on a search.Our in-depth evaluation demonstrate that smart_induct produces valuable recommendations across problem domains.Currently, smart_induct is an interactive tool; however, we expect that smart_induct can be used to narrow the search space of automatic inductive provers.
Yutaka Nagashima
FMCAD1
2020 Simple Dataset for Proof Method Recommendation in Isabelle/HOL
Yutaka Nagashima
CICM1
2019 LiFtEr: Language to Encode Induction Heuristics for Isabelle/HOL
Yutaka Nagashima
APLAS1
2018 PaMpeR: proof method recommendation system for Isabelle/HOL
abstract
Deciding which sub-tool to use for a given proof state requires expertise specific to each interactive theorem prover (ITP). To mitigate this problem, we present PaMpeR , a proof method recommendation system for Isabelle/HOL. Given a proof state, PaMpeR recommends proof methods to discharge the proof goal and provides qualitative explanations as to why it suggests these methods. PaMpeR generates these recommendations based on existing hand-written proof corpora, thus transferring experienced users’ expertise to new users. Our evaluation shows that PaMpeR correctly predicts experienced users’ proof methods invocation especially when it comes to special purpose proof methods.
Yutaka Nagashima, Yilun He
ASE1
2018 Goal-Oriented Conjecturing for Isabelle/HOL
Yutaka Nagashima, Julian Parsert
CICM1
2017 A Proof Strategy Language and Proof Script Generation for Isabelle/HOL
Yutaka Nagashima, Ramana Kumar
CADE1
2016 CoGENT: Verifying High-Assurance File System Implementations
abstract
We present an approach to writing and formally verifying high-assurance file-system code in a restricted language called Cogent, supported by a certifying compiler that produces C code, high-level specification of Cogent, and translation correctness proofs. The language is strongly typed and guarantees absence of a number of common file system implementation errors. We show how verification effort is drastically reduced for proving higher-level properties of the file system implementation by reasoning about the generated formal specification rather than its low-level C code. We use the framework to write two Linux file systems, and compare their performance with their native C implementations.
Sidney Amani, Alex Hixon, Zilin Chen, Christine Rizkallah, Peter Chubb, Liam O'Connor, Joel Beeren, Yutaka Nagashima, Japheth Lim, Thomas Sewell, Joseph Tuong, Gabriele Keller, Toby C. Murray, Gerwin Klein, Gernot Heiser
ASPLOS8
2016 Refinement through restraint: bringing down the cost of verification
abstract
We present a framework aimed at significantly reducing the cost of verifying certain classes of systems software, such as file systems. Our framework allows for equational reasoning about systems code written in our new language, Cogent. Cogent is a restricted, polymorphic, higher-order, and purely functional language with linear types and without the need for a trusted runtime or garbage collector. Linear types allow us to assign two semantics to the language: one imperative, suitable for efficient C code generation; and one functional, suitable for equational reasoning and verification. As Cogent is a restricted language, it is designed to easily interoperate with existing C functions and to connect to existing C verification frameworks. Our framework is based on certifying compilation: For a well-typed Cogent program, our compiler produces C code, a high-level shallow embedding of its semantics in Isabelle/HOL, and a proof that the C code correctly refines this embedding. Thus one can reason about the full semantics of real-world systems code productively and equationally, while retaining the interoperability and leanness of C. The compiler certificate is a series of language-level proofs and per-program translation validation phases, combined into one coherent top-level theorem in Isabelle/HOL.
Liam O'Connor, Zilin Chen, Christine Rizkallah, Sidney Amani, Japheth Lim, Toby C. Murray, Yutaka Nagashima, Thomas Sewell, Gerwin Klein
ICFP7
2016 A Framework for the Automatic Formal Verification of Refinement from Cogent to C
Christine Rizkallah, Japheth Lim, Yutaka Nagashima, Thomas Sewell, Zilin Chen, Liam O'Connor, Toby C. Murray, Gabriele Keller, Gerwin Klein
ITP3