Incremental Test Case Generation for UML-RT Models Using Symbolic Execution

Rapos, Eric J.; Dingel, Juergen

doi:10.1109/icst.2012.205

Cited by 8 publications

(2 citation statements)

References 4 publications

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“…Nevertheless, this tool does not fully support mix-and-match composition of components. Test generation is also supported in [57]. UML-RT models could be integrated with other models in the Gamma framework as UML-RT components and their composition can be expressed using the statechart language of Gamma.…”

Section: Related Workmentioning

confidence: 99%

Mixed-semantics composition of statecharts for the component-based design of reactive systems

et al. 2020

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The increasing complexity of reactive systems can be mitigated with the use of components and composition languages in model-driven engineering. Designing composition languages is a challenge itself as both practical applicability (support for different composition approaches in various application domains), and precise formal semantics (support for verification and code generation) have to be taken into account. In our Gamma Statechart Composition Framework, we designed and implemented a composition language for the synchronous, cascade synchronous and asynchronous composition of statechart-based reactive components. We formalized the semantics of this composition language that provides the basis for generating composition-related Java source code as well as mapping the composite system to a back-end model checker for formal verification and model-based test case generation. In this paper, we present the composition language with its formal semantics, putting special emphasis on design decisions related to the language and their effects on verifiability and applicability. Furthermore, we demonstrate the design and verification functionality of the composition framework by presenting case studies from the cyber-physical system domain.

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Section: Related Workmentioning

confidence: 99%

Mixed-semantics composition of statecharts for the component-based design of reactive systems

et al. 2020

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“…Existing work on the generation of test cases in the presence of evolving models is related to the generation of test input sequences from evolving state machines [ElFakih et al 2004;Pap et al 2007;Rapos and Dingel 2012] and does not deal with the generation of complex data structures.…”

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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