# Multi-model Consistency through Transitive Combination of Binary Transformations: Unterschied zwischen den Versionen

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− | |kurzfassung= | + | |kurzfassung=Software systems are usually described through multiple models that address different development concerns. These models can contain shared information, which leads to redundant representations of the same information and dependencies between the models. These representations of shared information have to be kept consistent, for the system description to be correct. The evolution of one model can cause inconsistencies with regards to other models for the same system. Therefore, some mechanism of consistency restoration has to be applied after changes occurred. Manual consistency restoration is error-prone and time-consuming, which is why automated consistency restoration is necessary. Many existing approaches use binary transformations to restore consistency for a pair of models, but systems are generally described through more than two models. To achieve multi-model consistency preservation with binary transformations, they have to be combined through transitive execution. |

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+ | In this thesis, we explore transitive combination of binary transformations and we study what the resulting problems are. We develop a catalog of six failure potentials that can manifest in failures with regards to consistency between the models. The knowledge about these failure potentials can inform a transformation developer about possible problems arising from the combination of transformations. One failure potential is a consequence of the transformation network topology and the used domain models. It can only be avoided through topology adaptations. Another failure potential emerges, when two transformations try to enforce conflicting consistency constraints. This can only be repaired through adaptation of the original consistency constraints. Both failure potentials are case-specific and cannot be solved without knowing which transformations will be combined. Furthermore, we develop two transformation implementation patterns to mitigate two other failure potentials. These patterns can be applied by the transformation developer to an individual transformation definition, independent of the combination scenario. For the remaining two failure potentials, no general solution was found yet and further research is necessary. | ||

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+ | We evaluate the findings with a case study that involves two independently developed transformations between a component-based software architecture model, a UML class diagram and its Java implementation. All failures revealed by the evaluation could be classified with the identified failure potentials, which gives an initial indicator for the completeness of our failure potential catalog. The proposed patterns prevented all failures of their targeted failure potential, which made up 70% of all observed failures, and shows that the developed implementation patterns are applicable and help to mitigate issues occurring from transitively combining binary transformations. | ||

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## Aktuelle Version vom 3. Dezember 2018, 19:30 Uhr

Vortragende(r) | Torsten Syma | |
---|---|---|

Vortragstyp | Masterarbeit | |

Betreuer(in) | Heiko Klare | |

Termin | Fr 14. Dezember 2018 | |

Vortragsmodus | ||

Kurzfassung | Software systems are usually described through multiple models that address different development concerns. These models can contain shared information, which leads to redundant representations of the same information and dependencies between the models. These representations of shared information have to be kept consistent, for the system description to be correct. The evolution of one model can cause inconsistencies with regards to other models for the same system. Therefore, some mechanism of consistency restoration has to be applied after changes occurred. Manual consistency restoration is error-prone and time-consuming, which is why automated consistency restoration is necessary. Many existing approaches use binary transformations to restore consistency for a pair of models, but systems are generally described through more than two models. To achieve multi-model consistency preservation with binary transformations, they have to be combined through transitive execution.
In this thesis, we explore transitive combination of binary transformations and we study what the resulting problems are. We develop a catalog of six failure potentials that can manifest in failures with regards to consistency between the models. The knowledge about these failure potentials can inform a transformation developer about possible problems arising from the combination of transformations. One failure potential is a consequence of the transformation network topology and the used domain models. It can only be avoided through topology adaptations. Another failure potential emerges, when two transformations try to enforce conflicting consistency constraints. This can only be repaired through adaptation of the original consistency constraints. Both failure potentials are case-specific and cannot be solved without knowing which transformations will be combined. Furthermore, we develop two transformation implementation patterns to mitigate two other failure potentials. These patterns can be applied by the transformation developer to an individual transformation definition, independent of the combination scenario. For the remaining two failure potentials, no general solution was found yet and further research is necessary. We evaluate the findings with a case study that involves two independently developed transformations between a component-based software architecture model, a UML class diagram and its Java implementation. All failures revealed by the evaluation could be classified with the identified failure potentials, which gives an initial indicator for the completeness of our failure potential catalog. The proposed patterns prevented all failures of their targeted failure potential, which made up 70% of all observed failures, and shows that the developed implementation patterns are applicable and help to mitigate issues occurring from transitively combining binary transformations. |