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On the Shortest Linear Straight-Line Program for Computing Linear Forms

  • Joan Boyar
  • Philip Matthews
  • René Peralta
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5162)

Abstract

We study the complexity of the Shortest Linear Program (SLP) problem, which is to minimize the number of linear operations necessary to compute a set of linear forms. SLP is shown to be NP-hard. Furthermore, a special case of the corresponding decision problem is shown to be Max SNP-Complete.

Algorithms producing cancellation-free straight-line programs, those in which there is never any cancellation of variables in GF(2), have been proposed for circuit minimization for various cryptographic applications. We show that such algorithms have approximation ratios of at least 3/2 and therefore cannot be expected to yield optimal solutions to non-trivial inputs.

Keywords

Approximation Algorithm Linear Form Approximation Ratio Vertex Cover Minimum Vertex Cover 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Joan Boyar
    • 1
  • Philip Matthews
    • 1
  • René Peralta
    • 2
  1. 1.Dept. of Math. and Computer ScienceUniversity of Southern Denmark 
  2. 2.Computer Security Division, Information Technology LaboratoryNIST 

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