Ecosystems

In the dynamic realm of software engineering, the tools, methodologies, and paradigms are in a constant state of evolution. Among the most influential forces driving this transformation is ML. While ML itself is a marvel of computational prowess, its true genius emerges when integrated into the broader software engineering ecosystems. This chapter delves into the nuances of embedding ML within an ecosystem. Ecosystems are groups of software that work together but are not connected at compile time. A well-known ecosystem is the PyTorch ecosystem, where a set of libraries work together in the context of ML. However, there is much more than that to ML ecosystems in software engineering.

From automated testing systems that learn from each iteration to recommendation engines that adapt to user behaviors, ML is redefining how software is designed, developed, and deployed. However, integrating ML into software engineering is not a mere plug-and-play operation. It demands a rethinking...