Microservice Architecture (MSA) is a popular approach to designing, implementing, and deploying complex software systems. However, MSA introduces inherent challenges associated with distributed systems—one of them is the detection and mitigation of security smells. This paper draws on recent works that identified and categorized security smells in MSAs to propose a novel end-to-end approach for resolving security smells in existing MSAs. To this end, the presented approach extends a modeling ecosystem for MSAs with (i) reconstruction capabilities that automatically map MSA source code to viewpoint-specific architecture models; (ii) validations that detect security smells from reconstructed models; and (iii) model refactorings that support the interactive resolution of security smells and solutions’ reflection back to source code. Our approach allows for (i) uncovering security smells, which originate from the combination of different places in source code with possibly heterogeneous purposes, technologies, and software languages; as well as (ii) clustering, reifying, and fixing smells using a level of abstraction that is directed towards MSA stakeholders. The applicability and effectiveness of our approach are evaluated utilizing a standard case study from MSA research.

In modern systems engineering, domain experts increasingly utilize models to define domain-specific viewpoints in a highly interdisciplinary context. Despite considerable advances in developing model composition techniques, their integration in a largely heterogeneous language landscape still poses a challenge. Until now, composition in practice mainly focuses on developing foundational language components or applying language composition in smaller scenarios, while the application to extensive, heterogeneous languages is still missing. In this paper, we report on our experiences of composing sophisticated modeling languages using different techniques simultaneously in the context of heterogeneous application areas such as assistive systems and cyber-physical systems in the Internet of Things. We apply state-of-the-art practices, show their realization, and discuss which techniques are suitable for particular modeling scenarios. Pushing model composition to the next level by integrating complex, heterogeneous languages is essential for establishing modeling languages for highly interdisciplinary development teams.

Domain-driven Design (DDD) is a model-based software design methodology, which focuses on close collaboration of domain experts and software engineers. It promotes to capture relevant domain concepts in domain models in order to define a ubiquitous language, whose terms are well understood by stakeholders and consistently used throughout the software engineering process. DDD is considered particularly useful in Microservice Architecture (MSA) engineering, because it specifies patterns to structure modeled domain concepts in isolated contexts. These contexts determine concepts' applicability and validity, and make relationships between domain concepts beyond context boundaries explicit. Consequently, DDD contexts may be used to prescribe microservices' granularities and interaction relationships. However, domain models are usually underspecified, which facilitates communication with domain experts, but hampers the derivation of microservice code.In this paper, we present a model-driven methodology towards deriving microservice code from underspecified domain models. It relies on a set of viewpoint-based MSA modeling languages, which respect the concerns of DevOps teams, and a set of automatic model transformations, which decrease modeling effort and systematize source code derivation. We validate the applicability of our methodology by means of two case studies.

Microservice Architecture (MSA) is a novel approach for the development and deployment of service-based software systems. MSA puts a strong emphasis on loose coupling and high cohesion of services. This increases service-specific independence, which is considered to result in a better scalability, adaptability, and quality of software architectures. Another perceived benefit of adopting MSA is technology heterogeneity. Microservice teams are free to employ the technologies they deem to be most appropriate for service implementation and operation. However, technology heterogeneity increases the number of technologies in a microservice architecture with the risk to introduce technical debt and steeper learning curves for team members. In this paper, we present an approach to streamline the usage of different technologies in MSA-based software systems. It employs Aspect-oriented Modeling to make technology decisions in microservice architectures explicit and enable reasoning about them. Therefore, a set of languages for model-driven microservice development is extended with means to define, modularize, and apply MSA technology aspects. The usage and characteristics of our approach are shown and discussed in the context of a case study from the mobility domain.