Software evaluation methodology of Node.js parallelism under variabilities in scalable systems.

The backbone of Node.js is a single-threaded event loop, so computationally intensive tasks are bound to the performance of a single core. Modules with different architectures have been built to provide parallelism and scaling. However, their properties differ, making them appropriate for different cases. In order to assist software engineers in choosing the most appropriate module in the most efficient way, we perform an empirical study to investigate the modules' characteristics and functionality, taking into account system variances. Crucially, we present and apply an evaluation methodology focusing on four aspects: compute-intensive task execution, sharing data, communication and overhead. The results suggest that instance type (Node.js thread vs. Node.js process) is not enough to decide the most appropriate one. We find that modules with the highest performance in most cases can sacrifice other aspects, such as support and/or functionality and/or performance in fewer cases, while platform variances play a significant part.