Automated Generation of Positive and Negative Tests for Parsers

Zelenov, Sergey; Zelenova, S. A.

doi:10.1007/11759744_13

Cited by 12 publications

(11 citation statements)

References 10 publications

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“…Test suites for complete grammars of some languages, such as COBOL [4], C, and Java [13], have been generated. There remains a question of whether the use of automated methods for generating semantics-oriented tests by the complete description of the static and dynamic semantics of a real programming language is justified from the practical standpoint, since the approaches discussed have been tested on subsets of real languages or on model programming languages.…”

Section: Discussionmentioning

confidence: 99%

“…The approach suggested in [13] is based on constructing, for each terminal symbol t, a set F t of possible terminal symbols that can immediately follow t in some phrase of the language. The approach uses also the complement N t of the set F t in the set of all terminal symbols.…”

Section: Testing Of Syntax Analyzermentioning

confidence: 99%

“…For this purpose, programs from the complement of the set of syntactically correct programs in the set of all possible chains of terminal symbols (negative tests for the syntax in the figure) are used. Automated generations of such programs and the coverage criteria for them are considered in [13].…”

Section: Testing Of Syntax Analyzermentioning

confidence: 99%

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Survey of compiler testing methods

Kossatchev

Posypkin

2005

Program Comput Soft

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Compilers are used for creating executable modules for programs written in high-level languages; therefore, the presence of errors in a compiler is a serious danger for the quality of the software developed with the use of this compiler. As in the case of any other software, testing is one of the most important methods of quality control and error detection in compilers. The survey is devoted to methods for generating, running, and checking the quality of compiler test suites, which are based on formal specifications of the programming language syntax and semantics.

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Section: Discussionmentioning

confidence: 99%

Section: Testing Of Syntax Analyzermentioning

confidence: 99%

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Survey of compiler testing methods

Kossatchev

Posypkin

2005

Program Comput Soft

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“…Existing approaches use context free grammars to generate both valid and invalid input data structures, but the existing approaches do not model the complex relationships among data fields [Hoffman et al 2009;Zelenov and Zelenova 2006]. Context free grammars, for example, cannot be used to model the SES-DAQ relationship that indicates that the sequenceCount of a Packet must be greater by one than the sequenceCount of the previous Packet.…”

Section: Related Workmentioning

confidence: 99%

Augmenting Field Data for Testing Systems Subject to Incremental Requirements Changes

Nardo

Pastore

Briand

2017

ACM Trans. Softw. Eng. Methodol.

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When testing data processing systems, software engineers often use real world data to perform system level testing. However, in the presence of new data requirements software engineers may no longer benefit from having real world data with which to perform testing. Typically, new test inputs complying with the new requirements have to be manually written.We propose an automated model-based approach that combines data modelling and constraint solving to modify existing field data to generate test inputs for testing new data requirements. The approach scales in the presence of complex and structured data, thanks to both the reuse of existing field data and the adoption of an innovative input generation algorithm based on slicing the model into parts.We validated the scalability and effectiveness of the proposed approach using an industrial case study. The empirical study shows that the approach scales in the presence of large amounts of structured and complex data. The approach can produce, within a reasonable time, test input data that is over ten times larger in size than the data generated with constraint solving only. We also demonstrate that the generated test inputs achieve more code coverage than the test cases implemented by experienced software engineers.

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“…There are grammar-based testing scenarios that clearly benefit from inclusion of negative test cases [29]. For instance, a parser for which no grammar-based parser description is available can only be tested for completeness with regard to reference grammar with positive test cases whereas testing for correctness would require negative test cases.…”

Section: Matching Algorithmmentioning

confidence: 99%

Comparison of Context-Free Grammars Based on Parsing Generated Test Data

Fischer

Lämmel

Zaytsev

2012

Software Language Engineering

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Abstract. There exist a number of software engineering scenarios that essentially involve equivalence or correspondence assertions for some of the context-free grammars in the scenarios. For instance, when applying grammar transformations during parser development-be it for the sake of disambiguation or grammar-class compliance-one would like to preserve the generated language. Even though equivalence is generally undecidable for context-free grammars, we have developed an automated approach that is practically useful in revealing evidence of nonequivalence of grammars and discovering correspondence mappings for grammar nonterminals. The approach is based on systematic test data generation and parsing. We discuss two studies that show how the approach is used in comparing grammars of open source Java parsers as well as grammars from the course work for a compiler construction class.

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Automated Generation of Positive and Negative Tests for Parsers

Cited by 12 publications

References 10 publications

Survey of compiler testing methods

Survey of compiler testing methods

Augmenting Field Data for Testing Systems Subject to Incremental Requirements Changes

Comparison of Context-Free Grammars Based on Parsing Generated Test Data

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