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Publication Detail
Highly Scalable Multi-Objective Test Suite Minimisation Using Graphics Card
  • Publication Type:
    Report
  • Authors:
    YOO S, Harman M, Ur S
  • Publisher:
    Department of Computer Science, University College London
  • publication date:
    13/03/2011
  • Place of publication:
    UK
  • Report number:
    RN/11/07
  • Status:
    Published
  • Keywords:
    gpgpu, test suite minimisation
Abstract
Search Based Software Engineering (SBSE) is an emerging paradigm in which search based optimisation algorithms are used to balance multiple software engineering objectives. The SBSE approach has been the subject of much recent interest. However, despite the fact that many optimisation algorithms are highly parallel, there has been very little work on exploiting this potential for scalability. This is an important oversight because scalability is so often a critical Software Engineering success factor. This paper shows how relatively inexpensive General Purpose computing on Graphical Processing Unit (GPGPU) can be used to run suitably adapted optimisation algorithms, opening up the possibility of cheap scalability. The paper develops a search based optimisation approach for multiple objective regression test optimisation, evaluating it on benchmark regression testing problems as well as larger real world problems. The results indicate that speed–ups of over 20x are possible using widely available standard GPUs. It is also encouraging that the results reveal a statistically strong correlation between larger problem instances and the degree of speed up achieved.
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