Recognizing standard computational structures (cliches) in a program can help an experienced programmer understand the program. We develop a graph parsing approach to automating program recognition in which programs and cliches are represented in an attributed graph grammar formalism and recognition is achieved by graph parsing. In studying this approach, we evaluate our representation's ability to suppress many common forms of variation which hinder recognition. We investigate the expressiveness of our graph grammar formalism for capturing programming cliches. We empirically and analytically study the computational cost of our recognition approach with respect to two medium-sized, real-world simulator programs.
| Identifer | oai:union.ndltd.org:MIT/oai:dspace.mit.edu:1721.1/6806 |
| Date | 01 July 1992 |
| Creators | Wills, Linda M. |
| Source Sets | M.I.T. Theses and Dissertation |
| Language | en_US |
| Detected Language | English |
| Format | 334 p., 55111115 bytes, 44699814 bytes, application/postscript, application/pdf |
| Relation | AITR-1358 |
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