Abstract
This article is a tutorial on how to achieve software evolution and adaptation in a dependable manner, by systematically applying formal modelling and verification. It shows how software can be designed upfront to tolerate different sources of uncertainty that cause continuous future changes. If possible changes can be predicted, and their occurrence can be detected, it is possible to design the software to be self-adaptable. Otherwise, continuous evolution has to be supported and continuous flow into operation has to be ensured. In cases where systems are designed to be continuously running, it is necessary to support safe continuous software deployment that guarantees correct operation in the presence of dynamic reconfigurations. The approaches we survey here have been mainly developed in the context of the SMScom project, funded by the European Commission –Programme IDEAS-ERC (http://erc-smscom.dei.polimi.it/.) – and lead by the author. It is argued that these approaches fit well the current agile methods for development and operations that are popularized as DevOps.
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Notes
- 1.
Note that this is often expressed as \(\mathcal {P}_{\bowtie p} F \varPhi \), using the finally operator.
- 2.
Actually we discussed the computation of the probability associated with the property, to which the constraint \(\bowtie p\) has to be applied.
- 3.
A proof can be found in [18].
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Ghezzi, C. (2016). Dependability of Adaptable and Evolvable Distributed Systems. In: Bernardo, M., De Nicola, R., Hillston, J. (eds) Formal Methods for the Quantitative Evaluation of Collective Adaptive Systems. SFM 2016. Lecture Notes in Computer Science(), vol 9700. Springer, Cham. https://doi.org/10.1007/978-3-319-34096-8_2
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