Enabling Consistency between Software Artefacts for Software Adaption and Evolution: Unterschied zwischen den Versionen

Aus SDQ-Institutsseminar
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|betreuer=Robert Heinrich
|betreuer=Robert Heinrich
|termin=Institutsseminar/2020-10-09
|termin=Institutsseminar/2020-10-09
|kurzfassung=Nowadays, software systems are evolving at a pace never seen before. As a result, emerging inconsistencies between different software artifacts are almost inevitable. Currently, there are already approaches for automated consistency maintenance between source code and architecture models. However, these approaches have various limitations. Therefore, in this thesis, we present a comprehensive approach for supporting the consistency preservation between software artifacts with special focus on software evolution and adaptation. At design time, source code analysis and consistency rules are used, while at run-time, monitoring data is used as input for a transformation pipeline. In contrast to already existing approaches, the automated derivation of the system composition is supported. Ultimately, self-validations were included as a central component of the approach. In a case study based evaluation the accuracy of the models and the performance of the approach was measured. In addition, the scalability of the transformations within the pipeline was also investigated.
|kurzfassung=Nowadays, software systems are evolving at a pace never seen before. As a result, emerging inconsistencies between different software artifacts are almost inevitable. Currently, there are already approaches for automated consistency maintenance between source code and architecture models. However, these approaches have various limitations. Therefore, in this thesis, we present a comprehensive approach for supporting the consistency preservation between software artifacts with special focus on software evolution and adaptation. At design-time, source code analysis and consistency rules are used, while at run-time, monitoring data is used as input for a transformation pipeline. In contrast to already existing approaches, the automated derivation of the system composition is supported. Ultimately, self-validations were included as a central component of the approach. In a case study based evaluation the accuracy of the models and the performance of the approach was measured. In addition, the scalability of the transformations within the pipeline was also investigated.
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Version vom 28. September 2020, 12:05 Uhr

Vortragende(r) David Monschein
Vortragstyp Masterarbeit
Betreuer(in) Robert Heinrich
Termin Fr 9. Oktober 2020
Vortragsmodus
Kurzfassung Nowadays, software systems are evolving at a pace never seen before. As a result, emerging inconsistencies between different software artifacts are almost inevitable. Currently, there are already approaches for automated consistency maintenance between source code and architecture models. However, these approaches have various limitations. Therefore, in this thesis, we present a comprehensive approach for supporting the consistency preservation between software artifacts with special focus on software evolution and adaptation. At design-time, source code analysis and consistency rules are used, while at run-time, monitoring data is used as input for a transformation pipeline. In contrast to already existing approaches, the automated derivation of the system composition is supported. Ultimately, self-validations were included as a central component of the approach. In a case study based evaluation the accuracy of the models and the performance of the approach was measured. In addition, the scalability of the transformations within the pipeline was also investigated.