A trajectory-based strict semantics for program slicing

  • Authors:

  • Richard W. Barraclough;David Binkley;Sebastian Danicic;Mark Harman;Robert M. Hierons;Ákos Kiss;Mike Laurence;Lahcen Ouarbya

  • Affiliations:

  • Department of Computing, Goldsmiths College, University of London, London SE14 6NW, UK;Computer Science Department, Loyola College, Baltimore MD 21210-2699, USA;Department of Computing, Goldsmiths College, University of London, London SE14 6NW, UK;Department of Computer Science, Kings College London WC2R 2LS, UK;School of Information Systems, Computing, and Mathematics, Brunel University, Uxbridge, Middlesex, UB8 3PH, UK;Department of Software Engineering, Institute of Informatics, University of Szeged, 6720 Szeged, Hungary;Department of Computing, Goldsmiths College, University of London, London SE14 6NW, UK;Department of Computing, Goldsmiths College, University of London, London SE14 6NW, UK

  • Venue:
  • Theoretical Computer Science
  • Year:
  • 2010

Quantified Score

Hi-index 5.23

Visualization

Abstract

We define a program semantics that is preserved by dependence-based slicing algorithms. It is a natural extension, to non-terminating programs, of the semantics introduced by Weiser (which only considered terminating ones) and, as such, is an accurate characterisation of the semantic relationship between a program and the slice produced by these algorithms. Unlike other approaches, apart from Weiser's original one, it is based on strict standard semantics which models the 'normal' execution of programs on a von Neumann machine and, thus, has the advantage of being intuitive. This is essential since one of the main applications of slicing is program comprehension. Although our semantics handles non-termination, it is defined wholly in terms of finite trajectories, without having to resort to complex, counter-intuitive, non-standard models of computation. As well as being simpler, unlike other approaches to this problem, our semantics is substitutive. Substitutivity is an important property because it greatly enhances the ability to reason about correctness of meaning-preserving program transformations such as slicing.