Microservice architectures (MSA) have become a dominant architectural style choice in the service oriented software industry. Because of this, as with any other system, some unoptimized approaches might creep into architectures. These are what we call anti-patterns, they can be considered the opposite of design patterns. Furthermore, a microservice architecture can quickly grow to an immense scale due to the number of services.

In this work, we present Luduan, a tool created within ING that provides engineers with insights into their MSA. Using different graph metrics and tracing data, we determine the likelihood of any service containing certain anti-patterns. We validate this methodology by gathering feedback from subject-matter experts, by ways of surveys and one-on-one sessions where Luduan is used as a support tool. Finally, we ask teams that are responsible for services, to figure out whether their service has an anti-pattern or not. We then use these results to fine tune the computations from metrics to anti-pattern likelihood.

Language workbenches are environments for simplifying the creation and use of computer languages. The annual Language Workbench Challenge (LWC) was launched in 2011 to allow the many academic and industrial researchers in this area an opportunity to quantitatively and qualitatively compare their approaches. We first describe all four LWCs to date, before focussing on the approaches used, and results generated, during the third LWC. We give various empirical data for ten approaches from the third LWC. We present a generic feature model within which the approaches can be understood and contrasted. Finally, based on our experiences of the existing LWCs, we propose a number of benchmark problems for future LWCs.

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