Automated Inference Techniques to Assist With the Construction of Self-Adaptive Software
S. Malek*; K. Canavera†; N. Esfahani‡ * University of California, Irvine, Irvine, CA, United States† George Mason University, Fairfax, VA, United States‡ Google Inc, Mountain View, CA, United States
Abstract
The state-of-the-art in engineering self-adaptive software systems involves manual construction of numerous models, which are then used at runtime for making and effecting adaptation decisions. For instance, predictive analytical models (e.g., queuing network models, Markov models) are constructed to assess the impact of adaptation choices on the system’s quality objectives (e.g., performance, reliability) at runtime. The construction ...
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