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Abstract-Microservices are a new trend rising fast from the enterprise world. Even though the design principles around microservices have been identified, it is difficult to have a clear view of existing research solutions for architecting microservices.In this paper we apply the systematic mapping study methodology to identify, classify, and evaluate the current state of the art on architecting microservices from the following three perspectives: publication trends, focus of research, and potential for industrial adoption. More specifically, we systematically define a classification framework for categorizing the research on architecting microservices and we rigorously apply it to the 71 selected studies. We synthesize the obtained data and produce a clear overview of the state of the art. This gives a solid basis to plan for future research and applications of architecting microservices.

Context: A microservice architecture is composed of a set of small services, each running in its own process and communicating with lightweight mechanisms. Many aspects on architecting with microservices are still unexplored and existing research is still far from being crispy clear. Objective: We aim at identifying, classifying, and evaluating the state of the art on architecting with microservices from the following perspectives: publication trends, focus of research, and potential for industrial adoption. Method: We apply the systematic mapping methodology. We rigorously selected 103 primary studies and we defined and applied a classification framework to them for extracting key information for subsequent analysis. We synthesized the obtained data and produced a clear overview of the state of the art. Results: This work contributes with (i) a classification framework for research studies on architecting with microservices, (ii) a systematic map of current research of the field, (iii) an evaluation of the potential for industrial adoption of research results, and (iv) a discussion of emerging findings and implications for future research. Conclusion: This study provides a solid, rigorous, and replicable picture of the state of the art on architecting with microservices. Its results can benefit both researchers and practitioners of the field.

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Microservices are gaining tremendous traction in industry and a growing scientific interest in academia. More and more companies are adopting this architectural style for modernizing their products and taking advantage of its promised benefits (e.g., agility, scalability). Unfortunately, the process of moving towards a microservice-based architecture is anything but easy, as there are plenty of challenges to address from both technical and organizational perspectives. In this paper we report about an empirical study on migration practices towards the adoption of microservices in industry. Specifically, we designed and conducted a survey targeting practitioners involved in the process of migrating their applications and we collected information (by means of interviews and questionnaires) on (i) the performed activities, and (ii) the challenges faced during the migration. Our findings benefit both (i) researchers by highlighting future directions for industryrelevant problems and (ii) practitioners by providing a reference framework for their (future) migrations towards microservices.

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Several research efforts from different areas have focused on the execution of UML models, resulting in a diverse and complex scientific body of knowledge. With this work, we aim at identifying, classifying, and evaluating existing solutions for the execution of UML models. We conducted a systematic review in which we selected 63 research studies and 19 tools among over 5400 entries by applying a systematic search and selection process. We defined a classification framework for characterizing solutions for UML model execution, and we applied it to the 82 selected entries. Finally, we analyzed and discussed the obtained data. From the analyzed data, we drew the following conclusions: (i) There is a growing scientific interest on UML model execution; (ii) solutions providing translational execution clearly outnumber interpretive solutions; (iii) model-level debugging is supported in very few cases; (iv) only a few research studies provide evidence of industrial use, with very limited empirical evaluations; (v) the most common limitation deals with coverage of the UML language. Based on these observations, we discuss potential research challenges and implications for the future of UML model execution. Our results provide a concise overview of states of the art and practice for UML model execution intended for use by both researchers and practitioners.

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