New experiments with a constraint-based approach to program plan matching
Alex Quilici, S. Woods, Yongjun Zhang · 2002
In earlier work, the authors presented some preliminary empirical scalability results for a constraint-based program plan matching algorithm. Those initial experiments had several important shortcomings: they worked with a collection of artificially generated programs, and they applied a particular; general-purpose constraint satisfaction approach. The paper reports the results of a collection of new experiments that begin to address these deficiencies. In particular they have begun experimenting with programs based on real-world C code, and they have begun exploring new constraint satisfaction algorithms that take advantage of the particular characteristics of the program understanding problem. While not definitive, these new experiments provide further support for their earlier results, and they have led to a new approach that provides significant improvements in the scalability of the plan matching algorithm.