Architectural Bad Smells for Self-Adaptive Systems: Go Runtime!

被引：0
|
作者：
dos Santos, Edilton Lima [1 ]
Schobbens, Pierre-Yves [1 ]
Machado, Ivan [2 ]
Perrouin, Gilles [1 ]
机构：
[1] Univ Namur, PReCISE, NaDI, Fac Comp Sci, Namur, Belgium
[2] Univ Fed Bahia, Inst Comp, Salvador, Brazil
来源：
17TH INTERNATIONAL WORKING CONFERENCE ON VARIABILITY MODELLING OF SOFTWARE-INTENSIVE SYSTEMS, VAMOS 2023 | 2023年
关键词：
Self-adaptive Systems; Software architecture; Architectural Smells; Architectural Quality; Runtime Validation;
D O I：
10.1145/3571788.3571802
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
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.
引用
收藏
页码：85 / 87
页数：3
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