Cloud computing and Infrastructure-as-Code (IaC), supported by technologies such as Docker, have shaped how many software systems are built and deployed. Previous research has identified typical issues for some types of IaC specification but not why they come to be, or they have delved into collaboration aspects but not into technical ones. This work aims to characterize the activities around two particular kinds of IaC specification—Dockerfiles and docker-compose.yml files. We seek to know how they can be better supported and therefore study also what approaches and tools practitioners employ. We used an online questionnaire to gather data. The first part of the study reached 68 graduate students from a study program on informatics engineering, and the second one 120 professional software developers. The results show that most of the activities of the process of developing a Dockerfile are perceived as time-consuming, especially when the respondents are beginners with this technology. We also found that solving issues using trial-and-error approaches is very common and that many developers do not use ancillary tools to support the development of Dockerfiles and docker-compose.yml files.

Systems are error-prone. Big systems have lots of errors. The Internet-of-Things poses us one of the biggest and widespread systems, where errors directly impact people's lives. Testing and validating is how one deals with errors; but testing and validating a planetary-scale, heterogeneous, and evergrowing ecosystem has its own challenges and idiosyncrasies. As of today, the solutions available for testing these systems are insufficient and fragmentary. In this paper we provide an overview on test approaches, tools and methodologies for the Internet-of-Things, its software and its devices. Our conclusion is that we are still lagging behind on the best practices and lessons learned from the Software Engineering community in the past decades.

The IoT area has grown significantly in the last few years and is expected to reach a gigantic amount of 50 billion devices by 2020. The appearance of serverless architectures, specifically highlighting FaaS, raises the question of the suitability of using them in IoT environments. Combining IoT with a serverless architectural design can effective when trying to make use of local processing power that exists in a local network of IoT devices and creating a fog layer that leverages computational capabilities that are closer to the end-user. In this approach, which is placed between the device and the serverless function, when a device requests for the execution of a serverless function will decide based on previous metrics of execution if the serverless function should be executed locally, in the fog layer of a local network of IoT devices, or if it should be executed remotely, in one of the available cloud servers. Therefore, this approach allows dynamically allocating functions to the most suitable layer.