Abstract
Macroprogramming's primary goal is to increase developers' productivity by providing high-level specifications of applications' behaviour at the system level. Macroprogramming may be a viable solution for developing complex IoT applications, such as those manipulating high data volume and heterogeneity. This paper updates a recent work identifying and analysing primary research on macroprogramming in IoT through a systematic literature mapping (SLM). We extended the search strategy scope by conducting an automatic search over five new databases and also performed the snowballing technique. As a result, besides the 38 studies group found in previous SLM, nine new papers were classified as relevant and rigorously analysed, totalising forty-seven studies. In comparison to previous work, results still point out the recurrence of abstractions in the network infrastructure, highlighting the use of frameworks in one-third of the applications and contributing with an overview of macroprogramming by researchers in different knowledge areas.
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