Assessing the impact of global variables on program dependence and dependence clusters

  • Authors:

  • David Binkley;Mark Harman;Youssef Hassoun;Syed Islam;Zheng Li

  • Affiliations:

  • King's College London, Centre for Research on Evolution, Search and Testing (CREST) Strand, London WC2R 2LS, UK;King's College London, Centre for Research on Evolution, Search and Testing (CREST) Strand, London WC2R 2LS, UK;King's College London, Centre for Research on Evolution, Search and Testing (CREST) Strand, London WC2R 2LS, UK;King's College London, Centre for Research on Evolution, Search and Testing (CREST) Strand, London WC2R 2LS, UK;King's College London, Centre for Research on Evolution, Search and Testing (CREST) Strand, London WC2R 2LS, UK

  • Venue:
  • Journal of Systems and Software
  • Year:
  • 2010

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Abstract

This paper presents results of a study of the effect of global variables on the quantity of dependence in general and on the presence of dependence clusters in particular. The paper introduces a simple transformation-based analysis algorithm for measuring the impact of globals on dependence. It reports on the application of this approach to the detailed assessment of dependence in an empirical study of 21 programs consisting of just over 50K lines of code. The technique is used to identify global variables that have a significant impact upon program dependence and to identify and characterize the ways in which global variable dependence may lead to dependence clusters. In the study, over half of the programs include such a global variable and a quarter have one that is solely responsible for a dependence cluster.