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Following the Dynamics of Structural Variants in Experimentally Evolved Populations
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Mutation testing with hyperproperties.

Andreas Fellner1, Mitra Tabaei Befrouei2, Georg Weissenbacher2

  • 1AIT Austrian Institute of Technology, Seibersdorf, Austria.

Software and Systems Modeling
|November 1, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces a novel mutation-driven test case generation method using hyperproperties. It enhances test generation for models by formalizing mutant killing criteria and enabling tool-based test case creation.

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Area of Science:

  • Software Engineering
  • Formal Methods
  • Software Testing

Background:

  • Mutation-driven testing is a key technique for assessing test suite effectiveness.
  • Existing methods often struggle with formalizing mutant killing criteria, especially for complex models.
  • Hyperproperties offer a powerful formalism for specifying properties over multiple system executions.

Purpose of the Study:

  • To present a new method for model-based mutation-driven test case generation.
  • To formalize the concept of mutant killing using hyperproperties for both deterministic and non-deterministic models.
  • To enable the generation of test cases using off-the-shelf hyperproperty model checking tools.

Main Methods:

  • Generation of mutants through syntactical modifications of the system under test (model or source code).
  • Formalization of mutant killing criteria using universal hyperproperties applicable to arbitrary reactive models.
  • Development of solutions to overcome model checking limitations, including model transformation and bounded SMT encoding.

Main Results:

  • Demonstrated the universality of the proposed hyperproperties for defining mutant killing.
  • Successfully generated test cases using an off-the-shelf hyperproperty model checker.
  • Evaluated the approach on various models across two different modeling languages.

Conclusions:

  • The proposed hyperproperty-based approach provides a robust and universal framework for mutation-driven test case generation.
  • The method enhances the automation and effectiveness of test generation for complex systems.
  • The integration with model checking tools and proposed solutions for limitations pave the way for practical application.