“Synthesizing input grammars”: a replication study

Author:

Bendrissou Bachir1,Gopinath Rahul1,Zeller Andreas1

Affiliation:

1. CISPA, Germany

Publisher

ACM

Reference22 articles.

1. [n. d.]. Artifact Review and Badging – Version 1.1. https://www.acm.org/publications/policies/artifact-review-and-badging-current [n. d.]. Artifact Review and Badging – Version 1.1. https://www.acm.org/publications/policies/artifact-review-and-badging-current

2. [n. d.]. GLADE Implementation and experiments. https://github.com/obastani/glade-full [n. d.]. GLADE Implementation and experiments. https://github.com/obastani/glade-full

3. [n. d.]. Grammars written for ANTLR v4. https://github.com/antlr/grammars-v4 [n. d.]. Grammars written for ANTLR v4. https://github.com/antlr/grammars-v4

4. Learning regular sets from queries and counterexamples

5. When won't membership queries help?

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1. V-Star: Learning Visibly Pushdown Grammars from Program Inputs;Proceedings of the ACM on Programming Languages;2024-06-20

2. ParDiff: Practical Static Differential Analysis of Network Protocol Parsers;Proceedings of the ACM on Programming Languages;2024-04-29

3. Fast Deterministic Black-box Context-free Grammar Inference;Proceedings of the IEEE/ACM 46th International Conference on Software Engineering;2024-04-12

4. Grammar Mutation for Testing Input Parsers (Registered Report);Proceedings of the 2nd International Fuzzing Workshop;2023-07-17

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