Code Complexity in Introductory Programming Courses

dc.contributor.author Ihantola, Petri
dc.contributor.author Petersen, Andrew
dc.date.accessioned 2019-01-03T01:03:31Z
dc.date.available 2019-01-03T01:03:31Z
dc.date.issued 2019-01-08
dc.description.abstract Instructors of introductory programming courses would benefit from having a metric for evaluating the sophistication of student code. Since introductory programming courses pack a wide spectrum of topics in a short timeframe, student code changes quickly, raising questions of whether existing software complexity metrics effectively reflect student growth as reflected in their code. We investigate code produced by over 800 students in two different Python-based CS1 courses to determine if frequently used code quality and complexity metrics (e.g., cyclomatic and Halstead complexities) or metrics based on length and syntactic complexity are more effective as a heuristic for gauging students' progress through a course. We conclude that the traditional metrics do not correlate well with time passed in the course. In contrast, metrics based on syntactic complexity and solution size correlate strongly with time in the course, suggesting that they may be more appropriate for evaluating how student code evolves in a course context.
dc.format.extent 9 pages
dc.identifier.doi 10.24251/HICSS.2019.924
dc.identifier.isbn 978-0-9981331-2-6
dc.identifier.uri http://hdl.handle.net/10125/60204
dc.language.iso eng
dc.relation.ispartof Proceedings of the 52nd Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Methods and Models
dc.subject Software Engineering Education and Training
dc.subject complexity measures, computer science educatio, CS1, curriculum, programming
dc.title Code Complexity in Introductory Programming Courses
dc.type Conference Paper
dc.type.dcmi Text
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