Activities per year
Abstract
Self-adaptive systems (SAS) change their behavior and structure at runtime to answer the changes in their environment. Such systems combine different architectural fragments or solutions via feature binding/unbinding at runtime. Moreover, this combination may negatively impact the system's architectural qualities, exhibiting architectural bad smells (ABS). These issues are challenging to detect in the code due to the combinatorial explosion of interactions amongst features. Since SAS do not document these features in their source code, design time smell detection ignores them and risks reporting smells that are different than those observed at runtime. This paper assesses this risk to understand how ABS occur at runtime for different feature combinations. We look for cyclic dependency and hub-like ABS in various runtime adaptations of two SAS, Adasim and mRubis. Our results indicate that architectural smells are feature-dependent and that their number is highly variable from one adaptation to the other. Some ABS appear in all runtime adaptations, some in only a few. We discuss the reasons behind these architectural smells for each system and draw some lessons for targeted analyses of ABS in SAS.
Original language | English |
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Pages | 1 |
Number of pages | 1 |
Publication status | Published - 13 Sept 2022 |
Event | The 21st Belgium-Netherlands Software Evolution Workshop - Université de Mons , Mons, Belgium Duration: 12 Sept 2022 → 13 Sept 2022 https://benevol2022.github.io/, |
Workshop
Workshop | The 21st Belgium-Netherlands Software Evolution Workshop |
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Abbreviated title | BENEVOL 2022 |
Country/Territory | Belgium |
City | Mons |
Period | 12/09/22 → 13/09/22 |
Internet address |
Keywords
- Architectural Smells
- Self-Adaptive Systems
- Behavioral Maps
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The 21st Belgium-Netherlands Software Evolution Workshop
Lima dos Santos, E. (Contributor)
12 Sept 2022 → 13 Sept 2022Activity: Participating in or organising an event types › Participation in workshop, seminar, course
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Abstract: Towards Assessing Architectural Smells for Self-Adaptive Systems at Runtime
Lima dos Santos, E. (Speaker)
13 Sept 2022Activity: Talk or presentation types › Oral presentation
Datasets
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Featured Scents: Towards Assessing ArchitecturalSmells for Self-Adaptive Systems at Runtime
Schobbens, P.-Y. (Contributor), Perrouin, G. (Contributor) & Lima dos Santos, E. (Contributor), Zenodo, 2022
DOI: 10.5281/zenodo.5814028, https://zenodo.org/record/5814028
Dataset