Some Experiments Toward Understanding How Program Plan Recognition Algorithms Scale
Steven Woods and
Alex
Quilici.
Abstract
Over the past decade, researchers in program understanding have formulated many
program understanding algorithms but have published few studies of their
relative scalability. Consequently, it is difficult to understand the relative
limitations of these algorithms and to determine whether the field of program
understanding is making progress. This paper attempts to address this
deficiency by formalizing the search strategies of several different program
understanding algorithms as constraint satisfaction problems, and by presenting
some preliminary empirical scalability results for these constraint-based
implementations. These initial results suggest that, at least under certain
conditions, constraint-based program understanding is close to being applicable
to real-world programs.
Awards, Comments
This paper was selected as the 1996 WCRE Outstanding Contribution.
Copyright Notice
Copyright 1996 IEEE. Published in the Proceedings of the IEEE Working
Conference on Reverse Engineering (WCRE-96), September, 1996, Monterey,
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The Paper