Automated Program Recognition by Graph Parsing
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 reco...
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| Language: | en_US |
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2004
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| Online Access: | http://hdl.handle.net/1721.1/6806 |
| _version_ | 1826191367224688640 |
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| author | Wills, Linda M. |
| author_facet | Wills, Linda M. |
| author_sort | Wills, Linda M. |
| collection | MIT |
| description | 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. |
| first_indexed | 2024-09-23T08:54:49Z |
| id | mit-1721.1/6806 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T08:54:49Z |
| publishDate | 2004 |
| record_format | dspace |
| spelling | mit-1721.1/68062019-04-10T19:40:58Z Automated Program Recognition by Graph Parsing Wills, Linda M. program understanding design recovery reverse engineering sdebugging documentation generation cliche recognition 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. 2004-10-20T19:57:30Z 2004-10-20T19:57:30Z 1992-07-01 AITR-1358 http://hdl.handle.net/1721.1/6806 en_US AITR-1358 334 p. 55111115 bytes 44699814 bytes application/postscript application/pdf application/postscript application/pdf |
| spellingShingle | program understanding design recovery reverse engineering sdebugging documentation generation cliche recognition Wills, Linda M. Automated Program Recognition by Graph Parsing |
| title | Automated Program Recognition by Graph Parsing |
| title_full | Automated Program Recognition by Graph Parsing |
| title_fullStr | Automated Program Recognition by Graph Parsing |
| title_full_unstemmed | Automated Program Recognition by Graph Parsing |
| title_short | Automated Program Recognition by Graph Parsing |
| title_sort | automated program recognition by graph parsing |
| topic | program understanding design recovery reverse engineering sdebugging documentation generation cliche recognition |
| url | http://hdl.handle.net/1721.1/6806 |
| work_keys_str_mv | AT willslindam automatedprogramrecognitionbygraphparsing |