activity
20162026
most citedLiFtEr: Language to Encode Induction Heuristics for Isabelle/HOL

7 citations · 25 across the 19 of their papers we have counts for

collaborators

19 papers

cs.LO2026

Abduction Prover in Isabelle/HOL

Yutaka Nagashima, Daniel Sebastian Goc

Proof assistants based on expressive logics suffer limited automation for proof search, raising the cost of formal verification based on proof assistants. We address this problem b…

cs.LO2023

Template-Based Conjecturing for Automated Induction in Isabelle/HOL

Yutaka Nagashima, Zijin Xu, Ningli Wang +2

Proof by induction plays a central role in formal verification. However, its automation remains as a formidable challenge in Computer Science. To solve inductive problems, human en…

cs.NE2022

Genetic Algorithm for Program Synthesis

Yutaka Nagashima

A deductive program synthesis tool takes a specification as input and derives a program that satisfies the specification. The drawback of this approach is that search spaces for su…

cs.PL2020

Definitional Quantifiers Realise Semantic Reasoning for Proof by Induction

Yutaka Nagashima

Proof assistants offer tactics to apply proof by induction, but these tactics rely on inputs given by human engineers. To automate this laborious process, we developed SeLFiE, a bo…

cs.PL2020

Faster Smarter Induction in Isabelle/HOL

Yutaka Nagashima

Proof by induction plays a critical role in formal verification and mathematics at large. However, its automation remains as one of the long-standing challenges in Computer Science…

cs.LO2020

Simple Dataset for Proof Method Recommendation in Isabelle/HOL (Dataset Description)

Yutaka Nagashima

Recently, a growing number of researchers have applied machine learning to assist users of interactive theorem provers. However, the expressive nature of underlying logics and esot…

cs.AI2020

Towards United Reasoning for Automatic Induction in Isabelle/HOL

Yutaka Nagashima

Inductive theorem proving is an important long-standing challenge in computer science. In this extended abstract, we first summarize the recent developments of proof by induction f…

cs.AI2020★ 1 cited

Smart Induction for Isabelle/HOL (System Description)

Yutaka Nagashima

Proof assistants offer tactics to facilitate inductive proofs. However, it still requires human ingenuity to decide what arguments to pass to those induction tactics. To automate t…

cs.LO2019

Domain-Specific Language to Encode Induction Heuristics

Yutaka Nagashima

Proof assistants, such as Isabelle/HOL, offer tools to facilitate inductive theorem proving. Isabelle experts know how to use these tools effectively; however, they did not have a…

cs.AI2019

Designing Game of Theorems

Yutaka Nagashima

"Theorem proving is similar to the game of Go. So, we can probably improve our provers using deep learning, like DeepMind built the super-human computer Go program, AlphaGo." Such…

cs.LO2019★ 7 cited

LiFtEr: Language to Encode Induction Heuristics for Isabelle/HOL

Yutaka Nagashima

Proof assistants, such as Isabelle/HOL, offer tools to facilitate inductive theorem proving. Isabelle experts know how to use these tools effectively; however, there is a little to…

cs.LO2019★ 1 cited

Towards Evolutionary Theorem Proving for Isabelle/HOL

Yutaka Nagashima

Mechanized theorem proving is becoming the basis of reliable systems programming and rigorous mathematics. Despite decades of progress in proof automation, writing mechanized proof…

cs.LO2018★ 1 cited

Towards Machine Learning Induction

Yutaka Nagashima

Induction lies at the heart of mathematics and computer science. However, automated theorem proving of inductive problems is still limited in its power. In this abstract, we first…

cs.LO2018★ 2 cited

Goal-Oriented Conjecturing for Isabelle/HOL

Yutaka Nagashima, Julian Parsert

We present PGT, a Proof Goal Transformer for Isabelle/HOL. Given a proof goal and its background context, PGT attempts to generate conjectures from the original goal by transformin…

cs.LO2018★ 1 cited

PaMpeR: Proof Method Recommendation System for Isabelle/HOL

Yutaka Nagashima, Yilun He

Deciding which sub-tool to use for a given proof state requires expertise specific to each ITP. To mitigate this problem, we present PaMpeR, a Proof Method Recommendation system fo…

cs.AI2017★ 3 cited

Towards Smart Proof Search for Isabelle

Yutaka Nagashima

Despite the recent progress in automatic theorem provers, proof engineers are still suffering from the lack of powerful proof automation. In this position paper we first report our…

cs.PL2016★ 3 cited

Close Encounters of the Higher Kind Emulating Constructor Classes in Standard ML

Yutaka Nagashima, Liam O'Connor

We implement a library for encoding constructor classes in Standard ML, including elaboration from minimal definitions, and automatic instantiation of superclasses.

cs.LO2016★ 2 cited

A Proof Strategy Language and Proof Script Generation for Isabelle/HOL

Yutaka Nagashima, Ramana Kumar

We introduce a language, PSL, designed to capture high level proof strategies in Isabelle/HOL. Given a strategy and a proof obligation, PSL's runtime system generates and combines…

cs.PL2016★ 4 cited

COGENT: Certified Compilation for a Functional Systems Language

Liam O'Connor, Christine Rizkallah, Zilin Chen +8

We present a self-certifying compiler for the COGENT systems language. COGENT is a restricted, polymorphic, higher-order, and purely functional language with linear types and witho…