Self-adaptive software systems stand out from traditional ones in that they are able to autonomously change their behavior and structure during their execution using one or more self-adaptation strategies. The main objective of such a strategy is to maintain or even improve the functionalities/qualities of the system despite uncertainty in its operational environment. To date, a number of self-adaptation strategies have been proposed-following the architectural, control-theoretic, or online search paradigm-for several application domains. However, it is still unclear when a particular self-adaptation strategy needs to be developed and when it needs to be used at runtime (when a system can choose among several available strategies). In this paper, we aim to answer the above questions by relying on the assessment of a strategy's costs (e.g., development effort, performance decrease) and benefits (e.g., re-usability, performance improvement) at design time and runtime. The main novelty is that we provide a holistic view over the return on investment of a strategy and propose that the system itself uses cost-benefit analysis to decide on which strategy to apply at runtime.

Gerostathopoulos, I., Raibulet, C., Alberts, E. (2022). Assessing Self-Adaptation Strategies Using Cost-Benefit Analysis. In 2022 IEEE 19th International Conference on Software Architecture Companion, ICSA-C 2022 (pp.92-95). Institute of Electrical and Electronics Engineers Inc. [10.1109/ICSA-C54293.2022.00023].

Assessing Self-Adaptation Strategies Using Cost-Benefit Analysis

Raibulet C.;
2022

Abstract

Self-adaptive software systems stand out from traditional ones in that they are able to autonomously change their behavior and structure during their execution using one or more self-adaptation strategies. The main objective of such a strategy is to maintain or even improve the functionalities/qualities of the system despite uncertainty in its operational environment. To date, a number of self-adaptation strategies have been proposed-following the architectural, control-theoretic, or online search paradigm-for several application domains. However, it is still unclear when a particular self-adaptation strategy needs to be developed and when it needs to be used at runtime (when a system can choose among several available strategies). In this paper, we aim to answer the above questions by relying on the assessment of a strategy's costs (e.g., development effort, performance decrease) and benefits (e.g., re-usability, performance improvement) at design time and runtime. The main novelty is that we provide a holistic view over the return on investment of a strategy and propose that the system itself uses cost-benefit analysis to decide on which strategy to apply at runtime.
paper
benefits; cost-benefit analysis; costs; return on investment; self-adaptation strategies; Self-adaptive systems;
English
19th IEEE International Conference on Software Architecture Companion, ICSA-C 2022 - 12 March 2022 through 15 March 2022
2022
2022 IEEE 19th International Conference on Software Architecture Companion, ICSA-C 2022
9781665494939
2022
92
95
reserved
Gerostathopoulos, I., Raibulet, C., Alberts, E. (2022). Assessing Self-Adaptation Strategies Using Cost-Benefit Analysis. In 2022 IEEE 19th International Conference on Software Architecture Companion, ICSA-C 2022 (pp.92-95). Institute of Electrical and Electronics Engineers Inc. [10.1109/ICSA-C54293.2022.00023].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/408236
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