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Hiroshi Unno

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Relational Cell Morphing: Automated Verification of Relational Properties of Array(…)ARRAY 20262026-06-16
The system reduces relational verification of array programs to constrained Horn clause solving over scalars by tracking a few distinguished cells across two…
Talk
A Hierarchy of Supermartingales for ω-Regular VerificationPLDI 20262026-06-15
Defines four new certificate classes and proves a strict hierarchy: GSSMs complete for positive recurrence, DVSSMs complete for null recurrence and the most…
Talk on
Supermartingales for Unique Fixed Points: A Unified Approach to Lower Bound VerificationPLDI 20262026-06-15
Presents a concrete criterion that turns uniqueness of least fixed points into a usable lower-bound proof: existence of a U-ranking supermartingale plus a…
Talk on
On Higher-Order Model Checking of Effectful Answer-Type-Polymorphic ProgramsOOPSLA 20252025-10-16
Claims decidability for a nontrivial fragment of effectful higher-order programs by introducing polymorphic answer-type □ and a type system that allows…
Talk on
Thrust: A Prophecy-Based Refinement Type System for RustPLDI 20252025-06-16
A new Rust verifier called Thrust implements a dependent refinement type system plus an inference pipeline that emits Constrained Horn Clauses to a CHC solver…
Talk on
Algebraic Temporal Effects: Temporal Verification of Recursively Typed Higher-Order(…)POPL 20252025-01-19
Proposes algebraic temporal effects: an axiomatized effect algebra plus an R modality for guarded recursive types that stratifies infinite behavior, an effect…
Talk
A Primal-Dual Perspective on Program Verification AlgorithmsPOPL 20252025-01-19
Presents a unified algorithmic framework that generalizes Lagrangians to discrete domains (powersets, predicates, ranking functions) and runs an abstract…
Talk
Higher-Order Model Checking of Effect-Handling Programs with Answer-Type ModificationOOPSLA 20242024-10-20
Claims decidability for higher-order model checking of programs with algebraic effect handlers by statically bounding the number of simultaneously active…
Talk on
Inductive Approach to SpacerPLDI 20242024-06-24
Presents a Spacer-like CHC solver derived by structural induction that replaces global quantifier elimination with an iterative, lazy use of model-based…
Talk on
Automating Relational Verification of Infinite-State ProgramsVMCAI 20242024-01-15
Two automated approaches appear: a constraint-based pipeline that encodes simultaneous synthesis of a semantic scheduler and relational invariant into an…
Talk on
Answer Refinement Modification: Refinement Type System for Algebraic Effects and...POPL 20242024-01-14
Proposes a refinement type system that tracks how delimited-continuation effects change return types via answer refinement modification, formalizes ATM/ARM…
Talk on
Temporal Verification with Answer-Effect Modification: Dependent Temporal Type-a...POPL 20232023-01-15
Extends a temporal type-and-effect system to handle delimited continuations (shift0/reset0) by tracking how continuations change the observable trace — the key…
Talk
Modular Primal-Dual Fixpoint Logic Solving for Temporal VerificationPOPL 20232023-01-15
Reduces μCLP validity to a predicate-constraint problem and leverages an existing solver to give a sound and relatively-complete decision method, then improves…
Talk
Optimal CHC Solving via Termination ProofsPOPL 20232023-01-15
Presents a new optimality checker that reduces CHC maximality to program termination, encodes termination-argument synthesis (angelic strategy and…
Talk
Software Model-Checking as Cyclic-Proof SearchSPLASH 20222022-12-05
Claims that many software model-checking procedures are just proof-search strategies for a cyclic proof system and gives a worked mapping: symbolic execution…
Talk
Software Model-Checking as Cyclic-Proof SearchPOPL 20222022-01-16
Claims that many software model-checking algorithms are exactly proof-search strategies for a cyclic proof system, so a single logical framework reconstructs…
Talk
Toward Neural-Network-Guided Program Synthesis and VerificationSAS 20212021-10-17
Proposes NeuGuS, a gray-box method that trains neural nets (four-layer; sometimes three-layer) then extracts inequalities from weights/biases to build Boolean…
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