Nearly a decade ago, ACM published the Computer Science Curricula 2013, which provided guidelines for undergraduate degree programs. One knowledge area within was Algorithms and Complexity, which also includes some data structures topics. While comprehensive, that list described far more material than would fit into a year-long undergraduate algorithms course, much less the single term common at most universities. The material within covers a large range of topics taught throughout undergraduate and graduate curricula. We present the results of the first large scale comprehensive survey of undergraduate introductory algorithms courses at institutions in the United States. We provide an overview of the instructors teaching algorithms, the concepts being taught, the ways students are evaluated, and the coursework students complete.

We find that algorithmic design paradigms and some preliminary data structures-related algorithms are very common and seem to form the core of algorithms education. In contrast, topics in analysis, computability, and advanced data structures and algorithms have more variance in where they are taught.

This paper serves as a snapshot for the current landscape of algorithms education. We envision the work will also assist curriculum designers, whether at the institutional or individual level, to compare their university’s offerings to a larger pool than their immediate circles may provide.