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Continuous monitoring of interactive exhibits in museums as part of a persuasive design approach
(2021)
IBH Living Lab AAL
(2021)
Coupling is one of the most frequently mentioned metric in software systems. However, to measure logical coupling between microservices, runtime information is needed or the availability of service-log files to analyze the calls between services is required. This work presents our emerging results, in which we propose a metric to statically calculate logical coupling between microservices based on commits to versioning systems. We performed an initial validation of the proposed metric with a dataset containing 145 open-source microservices projects. The results illustrate how logical coupling affects every system and increases overtime. However, we did not find a correlation between the number of commits or the number of developers and the introduction of logical coupling. In future, we investigate why, how, and when logical coupling is introduced in a system.
When it comes to improving the health of the general population, mHealth technologies with self-monitoring and intervention components hold a lot of promise. We argue, however, that due to various factors such as access, targeting, personal resources or incentives, self-monitoring applications run the risk of increasing health inequalities, thereby creating a problem of social justice. We review empirical evidence for “intervention-generated” inequalities, present arguments that self-monitoring applications are still morally acceptable, and develop approaches to avoid the promotion of health inequalities through self-monitoring applications.