No abstract

Simulation-based studies (SBS) have become an interesting investigation approach for Software Engineering (SE). However, the reports on experiments with dynamic simulation models found in the technical literature lack relevant information, hampering the full understanding of the procedures and results reported, as well as their replicability. Apart from the limitations on the length in conferences and journal papers, some of the relevant information seems to be missing due to methodological issues not considered when conducting such studies. This is the case of missing research questions and goals, lack of evidence regarding the dynamic simulation model validity, poorly designed simulation experiments, amongst others. Based on findings from a previous quasi-systematic literature review, we propose a set of reporting guidelines for SBS with dynamic models in the context of SE aiming at providing guidance on which information the report should contain. Furthermore, these guidelines were evolved to support SBS planning by identifying potential threats to simulation study validity and in making recommendations to avoid them, through qualitative analysis and external evaluation. Finally, we conducted different evaluations regarding both the reporting and planning guidelines, apart from using them to support the planning of a SBS as regards software evolution. A set of 33 reporting and planning guidelines for different stages of the simulation lifecycle and focused on the experimentation with dynamic simulation models have been put together. The first assessments point to a comprehensive set of guidelines, supporting a comprehensive preparation and review of the plans and reports from the studies, apart from the planning of a SBS focused on software evolution, potentially reducing the threats to the experimentation with the validity of dynamic simulation models. The 33 guidelines cannot be understood as separate groups for reporting and planning as they overlap in many aspects. The Empir Software Eng main goal is to use the guidelines to support the planning of a simulation-based study with dynamic models so that experimenters may identify potential threats to validity and produce relevant information for a complete simulation experiment report in advance. Despite their initial contribution to increase the validity of SBS, the reporting and planning of simulationbased experiments with dynamic models still has to be discussed and improved in SE. Therefore, additional assessments of this set of guidelines are needed to strengthen the confidence in their completeness and usefulness.

No abstract

The microservice architecture is claimed to satisfy ongoing software development demands, such as resilience, flexibility, and velocity. However, developing applications based on microservices also brings some drawbacks, such as the increased software operational complexity. Recent studies have also pointed out the lack of methods to prevent problems related to the maintainability of these solutions. Disregarding established design principles during the software evolution may lead to the so-called architectural erosion, which can end up in a condition of unfeasible maintenance. As microservices can be considered a new architecture style, there are few initiatives to monitoring the evolution of software microservice-based architectures. In this paper, we introduce the SYMBIOTE method for monitoring the coupling evolution of microservice-based systems. More specifically, this method collects coupling metrics during runtime (staging or production environments) and monitors them throughout software evolution. The longitudinal analysis of the collected measures allows detecting an upward trend in coupling metrics that could represent signs of architectural degradation. To develop the proposed method, we performed an experimental analysis of the coupling metrics behavior using artificially generated data. The results of these experiment revealed the metrics behavior in different scenarios, providing insights to develop the analysis method for the identification of architectural degradation. We evaluated the SYMBIOTE method in a real-case open source project called Spinnaker. The results obtained in this evaluation show the relationship between architectural changes and upward trends in coupling metrics for most of the analyzed release intervals. Therefore, the first version of SYMBIOTE has shown potential to detect signs of architectural degradation during the evolution of microservice-based architectures.

No abstract