Description: iObserve is an approach to cloud-based system adaptation and evolution through run-time observation and continuous quality analysis. With iObserve, run-time adaptation and evolution are two mutual, interwoven activities that influence each other. Central to iObserve is (a) the specification of the correspondence between observation results and design models, and (b) their use in both adaptation and evolution. Run-time observation data is promoted to meaningful values mapped to design models, thereby continuously updating and calibrating those design models during run-time while keeping the models comprehendible by humans. This engineering approach allows for automated adaptation at run-time and simultaneously supports software evolution. Model-driven software engineering is employed for various purposes such as monitoring instrumentation and model transformation.
R. Heinrich; Architectural Run-time Models for Performance and Privacy Analysis in Dynamic Cloud Applications. ACM SIGMETRICS Performance Evaluation Review, 43(4):13-22, ACM, 2016.
R. Heinrich, R. Jung, E. Schmieders, A. Metzger, W. Hasselbring, R. Reussner, K. Pohl; Architectural Run-Time Models for Operator-in-the-Loop Adaptation of Cloud Applications, In IEEE 9th Symposium on the Maintenance and Evolution of Service-Oriented Systems and Cloud-Based Environments, IEEE, 2015.
R. Heinrich, E. Schmieders, R. Jung, K. Rostami, A. Metzger, W. Hasselbring, R. Reussner, K. Pohl; Integrating Run-time Observations and Design Component Models for Cloud System Analysis, 9th Workshop on Models@run.time, pp. 41-46, CEUR Vol-1270, 2014.
W. Hasselbring, R. Heinrich, R. Jung, A. Metzger, K. Pohl, R. Reussner, E. Schmieders; iObserve: Integrated Observation and Modeling Techniques to Support Adaptation and Evolution of Software Systems, Technical Report CAU No. 1309, 2013.
Further publications can be found on the iObserve project web page.
Please email to Robert Heinrich for installation instructions.