A Teaching Assistant for the C Language (Short Paper)

Authors Rui C. Mendes , José João Almeida

Thumbnail PDF


  • Filesize: 0.49 MB
  • 8 pages

Document Identifiers

Author Details

Rui C. Mendes
  • Centro Algoritmi, Departamento de Informática, University of Minho, Braga, Portugal
José João Almeida
  • Centro Algoritmi, Departamento de Informática, University of Minho, Braga, Portugal

Cite AsGet BibTex

Rui C. Mendes and José João Almeida. A Teaching Assistant for the C Language (Short Paper). In Second International Computer Programming Education Conference (ICPEC 2021). Open Access Series in Informatics (OASIcs), Volume 91, pp. 13:1-13:8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)


We introduce a C tutor that can help instructors manage classes with many students learning to program in C. Nowadays, it is easy to evaluate code but it is hard to provide good feedback. We introduce a tool to help instructors provide students with feedback concerning their implementation and documentation for honing their programming skills. This tool is implemented in Python and is available at https://github.com/rcm/C_teaching_assistant.

Subject Classification

ACM Subject Classification
  • Applied computing → Computer-assisted instruction
  • Software and its engineering → Empirical software validation
  • Software metrics
  • Documentation extractor
  • Domain specific language
  • Query language
  • Report generation


  • Access Statistics
  • Total Accesses (updated on a weekly basis)
    PDF Downloads


  1. Sergey Astanin. Tabulate. https://pypi.org/project/tabulate/. Accessed: 2021-04-09.
  2. Rachel Cardell-Oliver. How can software metrics help novice programmers? In Proceedings of the Thirteenth Australasian Computing Education Conference-Volume 114, pages 55-62, 2011. Google Scholar
  3. Don Coleman, Dan Ash, Bruce Lowther, and Paul Oman. Using metrics to evaluate software system maintainability. Computer, 27(8):44-49, 1994. Google Scholar
  4. Francisco Jurado, Miguel A Redondo, and Manuel Ortega. Using fuzzy logic applied to software metrics and test cases to assess programming assignments and give advice. Journal of Network and Computer Applications, 35(2):695-712, 2012. Google Scholar
  5. Nadia Kasto and Jacqueline Whalley. Measuring the difficulty of code comprehension tasks using software metrics. In Proceedings of the Fifteenth Australasian Computing Education Conference-Volume 136, pages 59-65, 2013. Google Scholar
  6. Xavier Marcelet. Coverxygen. https://pypi.org/project/coverxygen/. Accessed: 2021-04-09.
  7. Thomas J McCabe. A complexity measure. IEEE Transactions on software Engineering, SE-2(4):308-320, 1976. URL: https://doi.org/10.1109/TSE.1976.233837.
  8. Simon, Andrew Luxton-Reilly, Vangel V. Ajanovski, Eric Fouh, Christabel Gonsalvez, Juho Leinonen, Jack Parkinson, Matthew Poole, and Neena Thota. Pass rates in introductory programming and in other stem disciplines. In Proceedings of the Working Group Reports on Innovation and Technology in Computer Science Education, ITiCSE-WGR '19, page 53–71, New York, NY, USA, 2019. Association for Computing Machinery. URL: https://doi.org/10.1145/3344429.3372502.
  9. Errol Thompson, Andrew Luxton-Reilly, Jacqueline L Whalley, Minjie Hu, and Phil Robbins. Bloom’s taxonomy for cs assessment. In Proceedings of the tenth conference on Australasian computing education-Volume 78, pages 155-161, 2008. Google Scholar
  10. Szymon Wasik, Maciej Antczak, Jan Badura, Artur Laskowski, and Tomasz Sternal. A survey on online judge systems and their applications. ACM Computing Surveys (CSUR), 51(1):1-34, 2018. Google Scholar
  11. Konrad Weihmann. Multimetric. https://pypi.org/project/multimetric/. Accessed: 2021-04-09.
Questions / Remarks / Feedback

Feedback for Dagstuhl Publishing

Thanks for your feedback!

Feedback submitted

Could not send message

Please try again later or send an E-mail