Architecture recovery is the process of obtaining the intended architecture of a software system by analyzing its implementation. Most existing architectural recovery approaches rely on extracting information about relationships between code entities and then use the extracted information to group closely related entities together. The approaches differ by the type of relationships they consider, e.g., method calls, data dependencies, and class name similarity. Prior work shows that combining multiple types of relationships during the recovery process is often beneficial as it leads to a better result than the one obtained by using the relationships individually. Yet, most, if not all, academic and industrial architecture recovery approaches simply unify the combined relationships to produce a more complete representation of the analyzed systems. In this paper, we propose and evaluate an alternative approach to combining information derived from multiple relationships, which is based on identifying agreements/disagreements between relationship types. We discuss advantages and disadvantages of both approaches and provide suggestions for future research in this area.

The microservice-based architecture - a SOA-inspired principle of dividing systems into components that communicate with each other using language-agnostic APIs - has gained increased popularity in industry. Yet, migrating a monolithic application to microservices is a challenging task. A number of automated microservice extraction techniques have been proposed to help developers with the migration complexity. These techniques, at large, construct a graph-based representation of an application and cluster its elements into service candidates. The techniques vary by their decomposition goals and, subsequently, types of relationships between application elements that they consider - structural, semantic term similarity, and evolutionary - with each technique utilizing a fixed subset and weighting of these relationship types.In this paper, we perform a multi-method exploratory study with 10 industrial practitioners to investigate (1) the applicability and usefulness of different relationships types during the microservice extraction process and (2) expectations practitioners have for tools utilizing such relationships. Our results show that practitioners often need a "what-if" analysis tool that simultaneously considers multiple relationship types during the extraction process and that there is no fixed way to weight these relationships. Our study also identifies organization- and application-specific considerations that lead practitioners to prefer certain relationship types over others, e.g., the age of the codebase and languages spoken in the organization. It outlines possible strategies to help developers during the extraction process, e.g., the ability to iteratively filter and customize relationships.