Generation of Positive and Negative Tests for Parsers

Zelenov, Sergey; Zelenova, S. A.

doi:10.1007/s11086-005-0040-6

Cited by 13 publications

(4 citation statements)

References 10 publications

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“…As a last example, and concrete application of all the above definitions, we introduce now G3, a context-free grammar representing a subset of a typical programming language 5 : we will see how advanced constraints look like, we will identify valid balanced weights and, finally, we will show a sample of generated sentences.…”

Section: Examplementioning

confidence: 99%

“…Where automatic test case generators differ from each other is the logic designed to select, between all rules expanding the same nonterminal, the rule to be used to substitute it: while such logic is typically designed to address a specific target coverage (examples are the already mentioned methodology introduced in [2] to address the production coverage, as well as the system introduced more recently in [5] to satisfy PLL coverage), within this paper all the presented approaches share the same logic, and this is simply and uniquely based on weights, introduced in Section 3.…”

Section: Introductionmentioning

confidence: 99%

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Introducing a Pure Weight-Based Concept for Automatic Test Case Generators

Bazzichi¹

2022

Preprint

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For decades, automatic test case generators driven by context-free grammars usually have adopted a derivation method designed to obtain the minimum set of shortest sentences.<div>Within this paper, a <i>pure weight-based</i> approach is described: such approach uniquely uses <i>weights </i>to select a rule while expanding a nonterminal symbol; we will assess how it is always possible to identify <i>balanced </i>weights which ensure the convergence of the process and we will see how the generated sentences are usually more complex than the shortest ones, and having additional chances to exercise the underlying system more extensively as confirmed by experimental results.</div>

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Section: Examplementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Introducing a Pure Weight-Based Concept for Automatic Test Case Generators

Bazzichi¹

2022

Preprint

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“…The main idea for the generation of positive and negative tests for parsers is to modify (mutate) the original grammar in order to obtain a language grammar that is similar to the original one but not equivalent to it. These mutant grammars are fed at the input of a test generator, which then produces potentially negative tests [2].…”

Section: Techniques For Parser Testing a Grammar-based Testing Tmentioning

confidence: 99%

“…In the context of compiler testing, a test case consists of a test purpose or test case description, a test input consisting of a source program for which the behavior of the compiler is being verified and an expected output which may include a reference to an output file or error file [1]. Also, the testing must cover positive as well as negative test cases [2]. The correctness of parsing affects all other parts of the compiler: verification of semantic constraints, optimizing transformations, and code generation.…”

Section: Introductionmentioning

confidence: 99%

Techniques for automated testing of Lola industrial robot language Parser

Lutovac¹,

Bojic²

2014

Telfor

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Abstract -The accuracy of parsing execution directly affects the accuracy of semantic analysis, optimization and object code generation. Therefore, parser testing represents the basis of compiler testing. It should include tests for correct and expected, but also for unexpected and invalid cases. Techniques for testing the parser, as well as algorithms and tools for test sentences generation, are discussed in this paper. The methodology for initial testing of a newly developed compiler is proposed. Generation of negative test sentences by modifying the original language grammar is described. Positive and negative test cases generated by Grow, Purdom's algorithm with and without length control, CDRC-P algorithm and CDRC-P algorithm with length control are applied to the testing of L-IRL robot programming language. For this purpose two different tools for generation of test sentences are used. Based on the presented analysis of possible solutions, the appropriate method can be chosen for testing the parser for smaller grammars with many recursive rules.

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