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ast-patterns:start [2018/07/04 18:33]
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ast-patterns:start [2018/07/04 18:36]
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| {{:papers:aied2017:aied2017.pdf|Automatic extraction of AST patterns for debugging student programs}} (2017). We propose using abstract-syntax-tree (AST) patterns as features for learning rules to distinguish between correct and incorrect programs. We evaluated our approach on past student programming data for a number of Prolog problems. For 31 out of 44 problems, the induced rules correctly classified over 85% of programs based only on their structural features. For approximately 73% of incorrect submissions, we were able to generate hints that were implemented by the student in some subsequent submission. | {{:papers:aied2017:aied2017.pdf|Automatic extraction of AST patterns for debugging student programs}} (2017). We propose using abstract-syntax-tree (AST) patterns as features for learning rules to distinguish between correct and incorrect programs. We evaluated our approach on past student programming data for a number of Prolog problems. For 31 out of 44 problems, the induced rules correctly classified over 85% of programs based only on their structural features. For approximately 73% of incorrect submissions, we were able to generate hints that were implemented by the student in some subsequent submission. |
| * Results ({{:papers:aied2017:results.tsv|.tsv}}, {{:papers:aied2017:results.ods|.ods}}) | * Results ({{:papers:aied2017:results.tsv|.tsv}}, {{:papers:aied2017:results.ods|.ods}}) |
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| | {{:papers:tlt2017:tlt2017.pdf|Rewrite rules for debugging student programs in programming tutors}} (2017). Before AST patterns we formalized the notion of a »code edit« to support automatic program rewriting, described in this paper. |
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