Towards a Model of API Learning
Caitlin L. Kelleher, Michelle Ichinco · 2019
In today’s world, learning new APIs (Application Programming Interfaces) is fundamental to being a programmer. Prior research suggests that programmers learn on-the-fly while they work on other project-related tasks. Yet, this process is often inefficient. This inefficiency has inspired research seeking to understand and improve API learnability. While the existing research has provided insight into API learning, we still have a fractured understanding of the process of learning a new API. In this paper, we take the first steps towards developing a theoretical model of API learning by combining predictions from Information Foraging Theory (IFT) to describe information search behavior, Cognitive Load Theory (CLT) to describe learning, and External Memory (EM) to describe how API learners augment their short term memories. Our proposed model is consistent with existing research on barriers to learning APIs and helps to provide explanations for these barriers as well as suggest new research directions.