DocumentCode :
635190
Title :
Managing non-functional uncertainty via model-driven adaptivity
Author :
Ghezzi, Carlo ; Pinto, Leandro Sales ; Spoletini, Paola ; Tamburrelli, Giordano
Author_Institution :
DeepSE, Politec. di Milano, Milan, Italy
fYear :
2013
fDate :
18-26 May 2013
Firstpage :
33
Lastpage :
42
Abstract :
Modern software systems are often characterized by uncertainty and changes in the environment in which they are embedded. Hence, they must be designed as adaptive systems. We propose a framework that supports adaptation to non-functional manifestations of uncertainty. Our framework allows engineers to derive, from an initial model of the system, a finite state automaton augmented with probabilities. The system is then executed by an interpreter that navigates the automaton and invokes the component implementations associated to the states it traverses. The interpreter adapts the execution by choosing among alternative possible paths of the automaton in order to maximize the system´s ability to meet its non-functional requirements. To demonstrate the adaptation capabilities of the proposed approach we implemented an adaptive application inspired by an existing worldwide distributed mobile application and we discussed several adaptation scenarios.
Keywords :
adaptive systems; finite state machines; mobile computing; probability; program interpreters; program verification; uncertainty handling; adaptive systems; distributed mobile application; finite state automaton; interpreter; model-driven adaptivity; nonfunctional uncertainty management; probabilities; software systems; system ability maximization; Abstracts; Automata; Measurement; Time factors; Uncertainty; Unified modeling language; Usability;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Software Engineering (ICSE), 2013 35th International Conference on
Conference_Location :
San Francisco, CA
Print_ISBN :
978-1-4673-3073-2
Type :
conf
DOI :
10.1109/ICSE.2013.6606549
Filename :
6606549
Link To Document :
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