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Cluster: A Fast Tool to Identify Groups of Similar Programs

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Computing and Combinatorics (COCOON 2002)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2387))

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Abstract

cluster is a tool to partition a large pool of C programs into groups according to structural similarity. Its method involves calculating an alignment score for each program against a mosaic made of randomly selected code fragments of fixed size from the pool. The scores are then grouped together so that the distance between two adjacent members of a group is at most some threshold value. cluster is effective in identifying tight clusters of similar programs and is capable of distributing its workload over a network of workstations to achieve very fast running times. As a tool, cluster is highly configurable: the user can adjust its alignment scoring scheme and clustering threshold as well as obtain visual alignments of programs suspected to be similar.

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA

    Casey Carter

  2. Department of Mathematics & Computer Science, Santa Clara University, Santa Clara, CA, 95053-0290, USA

    Nicholas Tran

Authors
  1. Casey Carter
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  2. Nicholas Tran
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Editor information

Editors and Affiliations

  1. Department of Computer Science, University of California, Santa Barbara, California, 93106, USA

    Oscar H. Ibarra

  2. Department of Mathematics, National University of Singapore, Singapore, Singapore, 117543

    Louxin Zhang

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© 2002 Springer-Verlag Berlin Heidelberg

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Carter, C., Tran, N. (2002). Cluster: A Fast Tool to Identify Groups of Similar Programs. In: Ibarra, O.H., Zhang, L. (eds) Computing and Combinatorics. COCOON 2002. Lecture Notes in Computer Science, vol 2387. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45655-4_22

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  • DOI: https://doi.org/10.1007/3-540-45655-4_22

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-43996-7

  • Online ISBN: 978-3-540-45655-1

  • eBook Packages: Springer Book Archive

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