Automatic Model-Based Generation of Parameterized Test Cases Using Data Abstraction | Zendy

Jens Calamé | Zendy; Natalia Ioustinova | Zendy; Jaco van de Pol | Zendy

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Automatic Model-Based Generation of Parameterized Test Cases Using Data Abstraction

Author(s) -

Jens Calamé,

Natalia Ioustinova,

Jaco van de Pol

Publication year - 2007

Publication title -

electronic notes in theoretical computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.242

H-Index - 60

ISSN - 1571-0661

DOI - 10.1016/j.entcs.2007.06.019

Subject(s) - computer science , abstraction , parameterized complexity , constraint (computer aided design) , test case , process (computing) , test data , test (biology) , programming language , theoretical computer science , test management approach , algorithm , machine learning , software development , software , mathematics , paleontology , philosophy , geometry , regression analysis , epistemology , biology , software construction

Developing test suites is a costly and error-prone process. Model-based test generation tools facilitate this process by automatically generating test cases from system models. The applicability of these tools, however, depends on the size of the target systems. Here, we propose an approach to generate test cases by combining data abstraction, enumerative test generation and constraint-solving. Given the concrete specification of a possibly infinite system, data abstraction allows to derive an abstract system, which is finite and thus suitable for the automatic generation of abstract test cases with enumerative tools. To execute abstract test cases, we have to instantiate them with concrete data. For data selection we make use of constraint-solving techniques

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