2013/01/20 by Prabhakar Ragde · 1 voice · 1 citation
Computer Science · Decision Sciences · #Distributed and Parallel Computing Systems #Scientific Computing and Data Management #Teaching and Learning Programming #cs.CY #cs.PL
paper · pdf · doi:10.4204/eptcs.106.3
published as EPTCS 106, 2013, pp. 40-49 · In Proceedings TFPIE 2012, arXiv:1301.4650
openalex publication_date 2013/01/20 · arxiv created 2013/01/22 · arxiv published 2013/01/22 · arxiv updated 2013/01/23 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/31
We commonly think of mathematics as bringing precision to application domains, but its relationship with computer science is more complex. This experience report on the use of Racket and Haskell to teach a required first university CS course to students with very good mathematical skills focusses on the ways that programming forces one to get the details right, with consequent benefits in the mathematical domain. Conversely, imprecision in mathematical abstractions and notation can work to the benefit of beginning programmers, if handled carefully.