CONTEST: a Controllable Test Matrix Toolbox for MATLAB

Alan Taylor, Desmond J. Higham, EPSRC Grants (Funder)

Research output: Contribution to journalArticlepeer-review

57 Citations (Scopus)
921 Downloads (Pure)


Large, sparse networks that describe complex interactions are a common feature across a number of disciplines, giving rise to many challenging matrix computational tasks. Several random graph models have been proposed that capture key properties of real-life networks. These models provide realistic, parametrized matrices for testing linear system and eigenvalue solvers. CONTEST (CONtrollable TEST matrices) is a random network toolbox for MATLAB that implements nine models. The models produce unweighted directed or undirected graphs; that is, symmetric or unsymmetric matrices with elements equal to zero or one. They have one or more parameters that affect features such as sparsity and characteristic pathlength and all can be of arbitrary dimension. Utility functions are supplied for rewiring, adding extra shortcuts and subsampling in order to create further classes of networks. Other utilities convert the adjacency matrices into real-valued coefficient matrices for naturally arising computational tasks that reduce to sparse linear system and eigenvalue problems.
Original languageEnglish
Pages (from-to)26:1-26:17
Number of pages17
JournalACM Transactions on Mathematical Software
Issue number4
Publication statusPublished - Feb 2009


  • matrix
  • real-life
  • networks
  • matlab
  • contest


Dive into the research topics of 'CONTEST: a Controllable Test Matrix Toolbox for MATLAB'. Together they form a unique fingerprint.

Cite this