2016
DOI: 10.1007/978-3-319-29198-7_11
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Higman’s Lemma and Its Computational Content

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Cited by 2 publications
(2 citation statements)
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“…become a major topic in proof theory, and today encompasses both proof mining [12,13,14], which focuses on obtaining quantitative information primarily from proofs in areas of mathematical analysis, and the mechanized synthesis of programs from proofs, which has found many concrete applications in discrete mathematics and computer science [3,4,40]. Though as far back as the 1950s Kreisel already discusses the use of proof theoretic techniques to extract quantitative information from proofs in abstract algebra [19], specifically Hilbert's 17th problem together with his Nullstellensatz, to date there are comparatively few formal applications of proof interpretations in algebra, the computational analysis of which is done largely on a case by case basis.…”
Section: Introductionmentioning
confidence: 99%
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“…become a major topic in proof theory, and today encompasses both proof mining [12,13,14], which focuses on obtaining quantitative information primarily from proofs in areas of mathematical analysis, and the mechanized synthesis of programs from proofs, which has found many concrete applications in discrete mathematics and computer science [3,4,40]. Though as far back as the 1950s Kreisel already discusses the use of proof theoretic techniques to extract quantitative information from proofs in abstract algebra [19], specifically Hilbert's 17th problem together with his Nullstellensatz, to date there are comparatively few formal applications of proof interpretations in algebra, the computational analysis of which is done largely on a case by case basis.…”
Section: Introductionmentioning
confidence: 99%
“…The extraction of programs from proofs has a long and rich history, dating back to Kreisel's pioneering work on the 'unwinding' of proofs [17,18]. In the ensuing decades, the application of proof interpretations in particular has become a major topic in proof theory, and today encompasses both proof mining [12,13,14], which focuses on obtaining quantitative information primarily from proofs in areas of mathematical analysis, and the mechanized synthesis of programs from proofs, which has found many concrete applications in discrete mathematics and computer science [3,4,40].…”
Section: Introductionmentioning
confidence: 99%