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Section: Software

Interval analysis libraries

ALIAS

Participants : David Daney, Jean-Pierre Merlet [correspondant] , Odile Pourtallier.

The ALIAS library (Algorithms Library of Interval Analysis for Systems), whose development started in 1998, is a collection of procedures based on interval analysis for systems solving and optimization.

ALIAS is made of two parts:

  • ALIAS-C++ : the C++ library (87 000 code lines) which is the core of the algorithms

  • ALIAS-Maple : the Maple interface for ALIAS-C++ (55 000 code lines). This interface allows one to specify a solving problem within Maple and get the results within the same Maple session. The role of this interface is not only to generate the C++ code automatically, but also to perform an analysis of the problem in order to improve the efficiency of the solver. Furthermore, a distributed implementation of the algorithms is available directly within the interface.

These libraries can be freely downloaded.

Int4Sci : a Scilab interface for interval analysis

Participants : David Daney, Gilles Trombettoni, Bertrand Neveu.

In 2006, we have started the development of a Scilab interface to C++ Bias/Profil interval arithmetic package and to the library ALIAS. The first version of Int4Sci has been released in 2008 – see http://www-sop.inria.fr/coprin/logiciels/Int4Sci/ for linux, MacOS and Windows. A second version, compatible with Scilab 5.3 is in preparation . This interface provides an interval arithmetic, basic interval manipulation tools as well as the solving of linear interval systems. All functions are documented and a tutorial is available.

Mathematica Interface to Interval Analysis

Participants : Yves Papegay [correspondant] , Jean-Pierre Merlet.

Since 2006, we have been implementing in Mathematica a high-level modular interface to the ALIAS library. The initial aim of providing the Mathematica users community a transparent access to the functionalities of ALIAS, and of extending the dissemination of our library, has progressively turned into the aim of providing ALIAS advanced users and developers with a high-level modular interface for prototyping, easy testing and quick implementation of new interval analysis algorithms and procedures relying on symbolic computation skills. This includes symbolic preprocessing of expressions, and symbolic specializations of interval analysis algorithms.