TXL: a rapid prototyping system for programming language dialects
Computer Languages
Lightweight source model extraction
SIGSOFT '95 Proceedings of the 3rd ACM SIGSOFT symposium on Foundations of software engineering
A systematic approach to fuzzy parsing
Software—Practice & Experience
JavaML: a markup language for Java source code
Proceedings of the 9th international World Wide Web conference on Computer networks : the international journal of computer and telecommunications netowrking
REVERE: Support for Requirements Synthesis from Documents
Information Systems Frontiers
Recovering documentation-to-source-code traceability links using latent semantic indexing
Proceedings of the 25th International Conference on Software Engineering
Generating Robust Parsers using Island Grammars
WCRE '01 Proceedings of the Eighth Working Conference on Reverse Engineering (WCRE'01)
Lightweight Impact Analysis using Island Grammars
IWPC '02 Proceedings of the 10th International Workshop on Program Comprehension
Syntactic Approximation Using Iterative Lexical Analysis
IWPC '03 Proceedings of the 11th IEEE International Workshop on Program Comprehension
An XML-Based Lightweight C++ Fact Extractor
IWPC '03 Proceedings of the 11th IEEE International Workshop on Program Comprehension
Identification of High-Level Concept Clones in Source Code
Proceedings of the 16th IEEE international conference on Automated software engineering
Improving Fact Extraction of Framework-Based Software Systems
WCRE '03 Proceedings of the 10th Working Conference on Reverse Engineering
An approach to program understanding by natural language understanding
Natural Language Engineering
Statistical decision-tree models for parsing
ACL '95 Proceedings of the 33rd annual meeting on Association for Computational Linguistics
Intricacies of Collins' Parsing Model
Computational Linguistics
Generating Software from Specifications
Generating Software from Specifications
Discriminative classifiers for deterministic dependency parsing
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
An Extensible Meta-Model for Program Analysis
IEEE Transactions on Software Engineering
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Program analysis tools used in software maintenance must be robust and ought to be accurate. Many data-driven parsing approaches developed for natural languages are robust and have quite high accuracy when applied to parsing of software. We show this for the programming languages Java, C/C++, and Python. Further studies indicate that post-processing can almost completely remove the remaining errors. Finally, the training data for instantiating the generic data-driven parser can be generated automatically for formal languages, as opposed to the manually development of treebanks for natural languages. Hence, our approach could improve the robustness of software maintenance tools, probably without showing a significant negative effect on their accuracy.