Change detection in hierarchically structured information
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
A forward move algorithm for LR error recovery
POPL '78 Proceedings of the 5th ACM SIGACT-SIGPLAN symposium on Principles of programming languages
Alignment of Trees - An Alternative to Tree Edit
CPM '94 Proceedings of the 5th Annual Symposium on Combinatorial Pattern Matching
Generation of Positive and Negative Tests for Parsers
Programming and Computing Software
Stratego/XT 0.17. A language and toolset for program transformation
Science of Computer Programming
WebDSL: A Case Study in Domain-Specific Language Engineering
Generative and Transformational Techniques in Software Engineering II
Practical Scope Recovery Using Bridge Parsing
Software Language Engineering
Natural and flexible error recovery for generated parsers
SLE'09 Proceedings of the Second international conference on Software Language Engineering
Specification of rewriting strategies
Algebraic'97 Proceedings of the 2nd international conference on Theory and Practice of Algebraic Specifications
A statistical analysis of syntax errors
Computer Languages
An algorithm for layout preservation in refactoring transformations
SLE'11 Proceedings of the 4th international conference on Software Language Engineering
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Evaluation of parse error recovery techniques is an open problem. The community lacks objective standards and methods to measure the quality of recovery results. This paper proposes an automated technique for recovery evaluation that offers a solution for two main problems in this area. First, a representative testset is generated by a mutation based fuzzing technique that applies knowledge about common syntax errors. Secondly, the quality of the recovery results is automatically measured using an oracle-based evaluation technique. We evaluate the validity of our approach by comparing results obtained by automated evaluation with results obtained by manual inspection. The evaluation shows a clear correspondence between our quality metric and human judgement.