Computational thinking, which centers around devising abstractions for problems so they can be solved with computational steps and efficient algorithms, is a concept that serves not only computer science (CS) but progressively more of science and everyday life. After Jeannette Wing published her influential paper on computational thinking,50 the discussion of computational thinking has greatly expanded in scale to include topics such as modeling natural processes as information processing.18
At the heart of computational thinking is abstraction, the primary subject of this essay. While abstractions have always been an essential part of computer science, the modern emphasis on computational thinking highlights their importance when teaching CS to a broad audience.
Abstractions play an important role in shaping virtually every field of science. However, in computer science, abstractions are not tethered to a physical reality, so we find useful abstractions pervading the field. For example, we shall encounter in Section 4 a vital abstraction from physics: quantum mechanics. There is a derived computing abstraction called quantum circuits, which starts with the physical ideas, but has led to programming languages for its simulation, to theoretical algorithms that exploit its unique capabilities and that one day may be implemented on a large-scale machine.
Every abstraction in computer science consists of the following: