This package contains the source and the test data for the paper Falk Hüffner. Algorithm Engineering for Optimal Graph Nipartization. Journal of Graph Algorithms and Applications, 13(2):77–98, 2009. http://dx.doi.org/10.7155/jgaa.00177 A slightly updated description is in the thesis Falk Hüffner. Algorithms and Experiments for Parameterized Approaches to Hard Graph Problems. PhD thesis, Institut für Informatik, Friedrich-Schiller-Universität Jena, 2007. http://hueffner.de/falk/diss-hueffner07.pdf Graph Bipartization solver ========================== The solver is written in ISO C99 plus a few Unix functions. To build the program, you need the GNU gcc compiler (version 3.2 or newer) and GNU make. Using other compilers or makes, or building on a non-Unix system, will probably require changes to the Makefile and the source. It has been tested on: * Debian GNU/Linux (i386) 3.1 with gcc 3.3.5 * Digital Unix 5.1 (Alpha) with 3.3.2 * Solaris 9 (UltraSPARC) with gcc 3.2 To compile, run "make". The program is called "occ". By default, it reads a graph from standard input and writes it to standard output. The graph format is a simple text format, where each line describes one edge, given by its two endpoints separated by whitespace: v0 v1 v1 v2 v2 v0 Vertex names can be any combination of letters, digits, and _. Note that this graph format cannot describe degree-0 vertices; however, they are irrelevant for Graph Bipartization anyway. The output is a minimum set of vertices to delete to make the graph bipartite. Example: # ./occ < data/afro-americans/10.graph 38 31 28 25 1 0 By default, the program executes the unmodified Reed/Smith/Vetta algorithm (see Table 1, column "Reed"). Option -g enables the use of Gray codes (column "OCC-Gray"), and option -b uses the "OCC-Enum2Col" algorithm. With -s, one gets only a single line of output containing some statistics: n m |C| run time [s] augmentations 102 307 11 0.78 671088 The test data ============= The directory "data" contains benchmark instances assembled by Sebastian Wernicke. They are based on data made available by the Whitehead Institute (http://www.broad.mit.edu/mpg/hapmap/hapstruc.html). See Sebastian Wernicke. On the algorithmic tractability of single nucleotide polymorphism (SNP) analysis and related problems. Diplomarbeit, Universität Tübingen, 2003. for details on the data and the file format. -- Falk Hüffner (http://hueffner.de/falk/), March 16 2005