Formalization and execution of linear algebra: From theorems to algorithms

  1. Aransay, J. 1
  2. Divasón, J. 1
  1. 1 Universidad de La Rioja
    info

    Universidad de La Rioja

    Logroño, España

    ROR https://ror.org/0553yr311

Revista:
Lecture Notes in Computer Science

ISSN: 0302-9743

Año de publicación: 2014

Volumen: 8901

Páginas: 1-18

Tipo: Artículo

DOI: 10.1007/978-3-319-14125-1_1 SCOPUS: 2-s2.0-84927601021 WoS: WOS:000354777900001 GOOGLE SCHOLAR

Otras publicaciones en: Lecture Notes in Computer Science

Resumen

In this work we present a formalization of the Rank Nullity theorem of Linear Algebra in Isabelle/HOL. The formalization is of interest because of various reasons. First, it has been carried out based on the representation of mathematical structures proposed in the HOL Multivariate Analysis library of Isabelle/HOL (which is part of the standard distribution of the proof assistant). Hence, our proof shows the adequacy of such an infrastructure for the formalization of Linear Algebra. Moreover, we enrich the proof with an additional formalization of its computational meaning; to this purpose, we choose to implement the Gauss-Jordan elimination algorithm for matrices over fields, prove it correct, and then apply the Isabelle code generation facility that permits to execute the formalized algorithm. For the algorithm to be code generated, we use again the implementation of matrices available in the HOL Multivariate Analysis library, and enrich it with some necessary features. We report on the precise modifications that we introduce to get code execution from the original representation, and on the performance of the code obtained. We present an alternative verified type refinement of vectors that outperforms the original version. This refinement performs well enough as to be applied to the computation of the rank of some biomedical digital images. Our work proves itself as a suitable basis for the formalization of numerical Linear Algebra in HOL provers that can be successfully applied for computations of real case studies. © Springer International Publishing Switzerland 2014