This article presents a microservice-based development approach, MSDeveloper (Microservices Developer), employing variability management for product configuration through a low-code development environment. The purpose of this approach is to offer a general-purpose environment for the easier development of families of products for different domains: a domain-oriented development environment is suggested, where domain developers and product developers can utilize the environment as a software ecosystem. Thus, genericity is offered through supporting different domains. A domain is populated with feature and process models and microservices in a layered architecture. Feature models drive the product configuration, which affects the process model and the microservice layer. An experimental study was conducted to validate the applicability of the approach and the usability of the development environment. Students from different courses were assigned system modeling projects where they utilized helper tools supporting the provided methodology. Furthermore, professional software developers were consulted about this recommended domain-oriented development environment. Feedback from student projects and professionals’ remarks are analyzed and discussed.

AUTORFPOWER software has been developed for automatic RF power measurement at microwave frequencies. In this study, the capabilities of AUTORFPOWER are explained and compared with commercial alternatives. The advantages of the developed software to metrological works and its contributions to future metrological R&D are discussed.

The calibration industry is renowned for its diverse and sophisticated equipment and complex processes, which necessitate innovative solutions to keep pace with rapidly advancing technology. This paper introduces an enhancement to an existing microservice-based cloud architecture, aimed at effectively managing the inherent complexity within this field. The enhanced architecture seamlessly integrates various equipment types and communication technologies, aligning diverse stakeholder expectations into a unified system that ensures efficient and accurate calibration processes. It highlights the integration of microservices to facilitate various methods of uncertainty calculation and the generation of digital calibration certificates (DCCs). A case study on RF power measurement illustrates the practical application and benefits of the enhanced architecture. Although initially focused on RF power measurement, the flexible architecture allows for future expansions to accommodate new standards and measurement techniques. The enhanced system offers a comprehensive approach to managing data flow from calibration equipment to the final generation of DCCs, utilizing cloud-based services for efficient data processing. As a future direction, this extension sets the groundwork for broader applicability across multiple measurement types, ensuring readiness for upcoming advancements in metrology.

RF power measurement is essential in RF and microwave metrology. For reliable and accurate power measurement, automatic measurement is preferred. A software application in C#, named AutoRFPower, was developed for automatic RF power measurement and uncertainty calculations at this study. According to the GUM document, this application is enhanced for uncertainty calculations by utilizing the Law of Propagation method and the Monte Carlo Simulation method. Trial measurements were performed at different RF power levels and frequencies between 50 MHz and 18 GHz using the AutoRFPower software. Law of Propagation and Monte Carlo Simulation uncertainty calculations were carried out by AutoRFPower based on the trial measurements and by the Oracle Crystal Ball simulation application. All measurements and their uncertainty calculations were compared with each other, and this study validated the uncertainty calculation of AutoRFPower. In addition, it was observed that in the Monte Carlo Simulation, uncertainty calculation results were non-symmetrical normal distribution, contrary to the assumption of symmetrical normal distribution according to the Low of Propagation method. Moreover, it has been observed that the statistical distribution of uncertainty changes depending on the dominant component of the parameters in the model function used for the uncertainty calculation with the Monte Carlo Simulation method.

Radio Frequency (RF) power sensor calibration is one of the essential measurements in RF and microwave metrology. For a reliable and accurate power sensor calibration, there are various methods, such as the substitution method, the direct comparison transfer method (DCTM), and the vector network analyzer (VNA)-based calibration method (VBCM). The VBCM is a method that is derived from the DCTM. It is a preferred method since the VNA has a better measurement capability and has fewer connection requirements for measurement devices. In this study, the milestones and potential application errors of the VBCM are given by considering the connection mistakes, measurement faults, calculation errors, and control software coding problems. At the end of the power sensor calibration measurements with the VBCM, the model function components and the uncertainty calculation examples according to the GUM Bayesian method are also presented in this study. In addition, the advantages and disadvantages of the VBCM compared to the former methods are discussed in this study.