Test criteria for context-free grammars

Li, Hu; Maozhong, Jin; Liu, Chao; Zhong-yi, Gao

doi:10.1109/cmpsac.2004.1342847

Cited by 4 publications

(1 citation statement)

References 7 publications

(8 reference statements)

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“…The purpose is to recover "lost" grammars of programming languages effectively. Other work [Li et al 2004] also targets testing the grammar, rather than the parser.…”

Section: Related Workmentioning

confidence: 99%

Regenerate: a language generator for extended regular expressions

RadanneGabriel

ThiemannPeter

2020

SIGPLAN Not.

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Regular expressions are part of every programmer’s toolbox. They are used for a wide variety of language-related tasks and there are many algorithms for manipulating them. In particular, matching algorithms that detect whether a word belongs to the language described by a regular expression are well explored, yet new algorithms appear frequently. However, there is no satisfactory methodology for testing such matchers. We propose a testing methodology which is based on generating positive as well as negative examples of words in the language. To this end, we present a new algorithm to generate the language described by a generalized regular expression with intersection and complement operators. The complement operator allows us to generate both positive and negative example words from a given regular expression. We implement our generator in Haskell and OCaml and show that its performance is more than adequate for testing.

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“…The purpose is to recover "lost" grammars of programming languages effectively. Other work [Li et al 2004] also targets testing the grammar, rather than the parser.…”

Section: Related Workmentioning

confidence: 99%

Regenerate: a language generator for extended regular expressions

RadanneGabriel

ThiemannPeter

2020

SIGPLAN Not.

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A Systematic Framework for Grammar Testing

Zheng¹,

Chen²

2009

2009 Eighth IEEE/ACIS International Conference on Computer and Information Science

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Grammars, especially context-free grammars, are widely used within and even outside the field of computer science. In this paper, we present a systematic framework for grammar testing, in which some commonly used techniques for testing programs such as module testing and integration testing are adapted and applied to the testing of grammars. We propose a nonterminal-based approach for grammar modularization, combined with an iterative process for grammar testing in which a grammar is tested with respect to both a generator and a recognizer. Experiments on grammars for some non-trivial programming languages such as C and Java demonstrate the feasibility and efficiency of the testing framework and the proposed approaches.

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