Abstract
The process of developing Dockerfiles is perceived by many developers as slow and based on trial-and-error, and it is hardly immediate to see the result of a change introduced into a Dockerfile. In this work we propose a plugin for Visual Studio Code, which we name Dockerlive, and that has the purpose of shortening the length of feedback loops. Namely, the plugin is capable of providing information to developers on a number of Dockerfile elements, as the developer is writing the Dockerfile. We achieve this through dynamic analysis of the resulting container, which the plugin builds and runs in the background. © 2022 IEEE.

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Abstract
Visualizations for Streaming Big Data need to handle high volumes of information in real-time, making it challenging to convey significant data changes without confusing users. A simple first approach would be switching from the current visual idiom to another, highlighting a significant change. Unfortunately, there are no guidelines to design effective transitions between two visual idioms in Streaming Big Data. Therefore, we created a tree of animation concepts to serve as a starting point for designing such animated transitions. The concepts represent several ways in which a visual idiom can be transformed into another. We chose three visual idioms to test our idea and arranged several concepts to apply at each possible pairing (six possibilities). For each pairing, we tested the accuracy of people's perceptions. Finally, we conducted a user study with 100 participants, where each participant answered various questions about transitions between two visual idioms shown in several videos. We concluded that to conceive appropriate animated transitions for Streaming Big Data (which also applies just for Data Streaming) that allow users to understand the changes in incoming data, varying how the proposed concepts are applied is not enough, highlighting the need for future research to address this challenge.

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