Computational Thinking in a Liberal Arts Cryptology Course

We describe aspects of computational thinking as covered in the course Codes and Ciphers (CSC 233). 1 Cryptology and Computational Thinking Cryptology consists of cryptography and cryptanalysis, or, in other words, the making and the breaking of ciphers. History suggests that one cannot successfully do one without the other: too many ciphers were designed by enthusiasts without any knowledge of cryptanalysis, and the consequences were typically dire. In our Codes and Ciphers courses, the breaking of ciphers is therefore a central part of discussion and student activity. Historically too, the breaking of ciphers has typically been the motor of advances in cryptography, including AlKindi’s description in 900 AD of how to use frequency analysis to break substitution ciphers in Arabic and the work of Bletchley Park on breaking the German Enigma cipher during World War II. Throughout history, the cryptographic process has become more algorithmic, as ciphers became more mechanical, mathematical, and, eventually, digital. But even before the mechanization of cryptography in the 19th century (not accidentally coinciding with the advent of computing machines, both analogue and digital), a cryptographer’s work was best described in algorithmic terms, and in Codes and Ciphers the students will see evidence of that when breaking many classical ciphers. The following is not a complete account of the topics covered in Codes and Ciphers; it concentrates on some of the relevant examples, and it recasts them in a more systematic fashion to emphasize the computational thinking lessons. For the purposes of this document, computational thinking is understood (narrowly) as the way of thinking involved in effective problem solving. No attempt is made to explain the ciphers discussed in detail; Simon Singh’s The Code Book is a good, popular introduction; it is also, currently, the textbook for the course.