Many Internet of Things and embedded projects are event driven, and therefore require asynchronous and concurrent programming. Current proposals for C++20 suggest that coroutines will have native language support. It is timely to survey the current use of coroutines in embedded systems development. This article investigates existing research which uses or describes coroutines on resource-constrained platforms. The existing research is analysed with regard to: software platform, hardware platform, and capacity; use cases and intended benefits; and the application programming interface design used for coroutines. A systematic mapping study was performed, to select studies published between 2007 and 2018 which contained original research into the application of coroutines on resource-constrained platforms. An initial set of 566 candidate papers, collated from on-line databases, were reduced to only 35 after filters were applied, revealing the following taxonomy. The C 8 C++ programming languages were used by 22 studies out of 35. As regards hardware, 16 studies used 8- or 16-bit processors while 13 used 32-bit processors. The four most common use cases were concurrency (17 papers), network communication (15), sensor readings (9), and data flow (7). The leading intended benefits were code style and simplicity (12 papers), scheduling (9), and efficiency (8). A wide variety of techniques have been used to implement coroutines, including native macros, additional tool chain steps, new language features, and non-portable assembly language. We conclude that there is widespread demand for coroutines on resource-constrained devices. Our findings suggest that there is significant demand for a formalised, stable, well-supported implementation of coroutines in C++, designed with consideration of the special needs of resource-constrained devices, and further that such an implementation would bring benefits specific to such devices.

Recent GPS-enabled mobile phones provide a rich and novel platform for exploring new kinds of educational software. Moreover, powerful high-level programming languages such as Python allow rapid development of learning tools that take advantage of mobile technology. This paper reports on a recent pilot study using mobile phones as situated learning tools. The study focused on expressing Dijkstra's algorithm for solving the classical graph theory problem, "single source shortest paths", in the form of problem-based learning and kinesthetic learning for non-IT university-level students. The objective of the pilot study was to find out if non-IT students could learn how to find shortest paths for simple graphs using mobile phone technology. The mobile phone's internal GPS system was used to guide how a student explored the problem, as they developed an understanding about shortest paths. The pilot study results indicate students enjoyed the experience and learned about finding shortest paths.