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Self-adaptive systems (SAS) change their behavior and structure at runtime depending on environmental changes or user requests. For this purpose, the SASs combine architectural fragments or solutions in their adaptation process. However, this process may negatively impact the system’s architectural qualities, exhibiting architectural bad smells (ABS). Current studies perform ABS detection for SAS at design time, ignoring their intrinsic runtime variability. We demonstrate that this ignorance leads to inaccurate smell detections and possibly wrong maintenance decisions. We delineate the challenges runtime variability raise on ABS detection and argue that we should analyze SAS architectures at runtime.
|Title of host publication||Proceedings of the 17th International Working Conference on Variability Modelling of Software-Intensive Systems, VaMoS 2023, Odense, Denmark, January 25-27, 2023|
|Subtitle of host publication||17th International Working Conference on Variability Modelling of Software-Intensive Systems|
|Editors||Myra B. Cohen, Thomas Thüm, Jacopo Mauro|
|Number of pages||3|
|Publication status||Published - 25 Jan 2023|
|Name||ACM International Conference Proceeding Series|
- Architectural Quality
- Architectural Smells
- Runtime Validation.
- Self-Adaptive Systems
- Software architecture
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17th International Working Conference on Variability Modelling of Software-Intensive Systems
Edilton Lima dos Santos (Contributor)25 Jan 2023 → 27 Jan 2023
Activity: Participating in or organising an event types › Participation in conference
Architectural Bad Smells for Self-Adaptive Systems: Go Runtime!
Edilton Lima dos Santos (Speaker)26 Jan 2023
Activity: Talk or presentation types › Oral presentation