Efficient Structural Analysis of Source Code for Large Scale Applications in Education

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandAufsatz in KonferenzbandForschungPeer-Review

Autoren

  • Adrian Kögl
  • Peter Hubwieser
  • Mike Talbot
  • Johannes Krugel
  • Michael Striewe
  • Michael Goedicke

Externe Organisationen

  • Columbia University
  • Technische Universität München (TUM)
  • Universität Duisburg-Essen
Forschungs-netzwerk anzeigen

Details

OriginalspracheEnglisch
Titel des SammelwerksProceedings of the 2022 IEEE Global Engineering Education Conference, EDUCON 2022
Herausgeber/-innenMohammed Jemni, Ilhem Kallel, Abdeljalil Akkari
Herausgeber (Verlag)IEEE Computer Society
Seiten24-30
Seitenumfang7
ISBN (elektronisch)9781665444347
ISBN (Print)978-1-6654-4435-4
PublikationsstatusVeröffentlicht - 2022
Veranstaltung13th IEEE Global Engineering Education Conference, EDUCON 2022 - Tunis, Tunesien
Dauer: 28 März 202231 März 2022

Publikationsreihe

NameIEEE Global Engineering Education Conference, EDUCON
Band2022-March
ISSN (Print)2165-9559
ISSN (elektronisch)2165-9567

Abstract

Automated Assessment Systems (AAS) are increasingly used in large computer science lectures to evaluate student solutions to programming assignments. The AAS normally carries out static and dynamic analysis of the program code. In addition, simple forms of learning analytics can often be generated quite easily. However, structural analyses and comparison of solutions for larger sets of student programs are, in many cases, complicated and time-consuming. In this article, we introduce a methodology with which thousands of programs can be analyzed in less than a second, for example, to search for the use of certain control structures or the application of recursion. For this purpose, we have developed a software that creates a structural representation for each programming solution in the form of a TGraph, which is inserted into a graph database using Neo4j. On this database, we can search for structural features by queries in the language Cypher. We have tested this methodology extensively for Java programs, measured its performance, and validated the results. Our software can also be applied to programs in other programming languages, such as Scratch. Additionally, we plan to make our software available to the community.

ASJC Scopus Sachgebiete

Zitieren

Efficient Structural Analysis of Source Code for Large Scale Applications in Education. / Kögl, Adrian; Hubwieser, Peter; Talbot, Mike et al.
Proceedings of the 2022 IEEE Global Engineering Education Conference, EDUCON 2022. Hrsg. / Mohammed Jemni; Ilhem Kallel; Abdeljalil Akkari. IEEE Computer Society, 2022. S. 24-30 (IEEE Global Engineering Education Conference, EDUCON; Band 2022-March).

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandAufsatz in KonferenzbandForschungPeer-Review

Kögl, A, Hubwieser, P, Talbot, M, Krugel, J, Striewe, M & Goedicke, M 2022, Efficient Structural Analysis of Source Code for Large Scale Applications in Education. in M Jemni, I Kallel & A Akkari (Hrsg.), Proceedings of the 2022 IEEE Global Engineering Education Conference, EDUCON 2022. IEEE Global Engineering Education Conference, EDUCON, Bd. 2022-March, IEEE Computer Society, S. 24-30, 13th IEEE Global Engineering Education Conference, EDUCON 2022, Tunis, Tunesien, 28 März 2022. https://doi.org/10.1109/educon52537.2022.9766748
Kögl, A., Hubwieser, P., Talbot, M., Krugel, J., Striewe, M., & Goedicke, M. (2022). Efficient Structural Analysis of Source Code for Large Scale Applications in Education. In M. Jemni, I. Kallel, & A. Akkari (Hrsg.), Proceedings of the 2022 IEEE Global Engineering Education Conference, EDUCON 2022 (S. 24-30). (IEEE Global Engineering Education Conference, EDUCON; Band 2022-March). IEEE Computer Society. https://doi.org/10.1109/educon52537.2022.9766748
Kögl A, Hubwieser P, Talbot M, Krugel J, Striewe M, Goedicke M. Efficient Structural Analysis of Source Code for Large Scale Applications in Education. in Jemni M, Kallel I, Akkari A, Hrsg., Proceedings of the 2022 IEEE Global Engineering Education Conference, EDUCON 2022. IEEE Computer Society. 2022. S. 24-30. (IEEE Global Engineering Education Conference, EDUCON). doi: 10.1109/educon52537.2022.9766748
Kögl, Adrian ; Hubwieser, Peter ; Talbot, Mike et al. / Efficient Structural Analysis of Source Code for Large Scale Applications in Education. Proceedings of the 2022 IEEE Global Engineering Education Conference, EDUCON 2022. Hrsg. / Mohammed Jemni ; Ilhem Kallel ; Abdeljalil Akkari. IEEE Computer Society, 2022. S. 24-30 (IEEE Global Engineering Education Conference, EDUCON).
Download
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abstract = "Automated Assessment Systems (AAS) are increasingly used in large computer science lectures to evaluate student solutions to programming assignments. The AAS normally carries out static and dynamic analysis of the program code. In addition, simple forms of learning analytics can often be generated quite easily. However, structural analyses and comparison of solutions for larger sets of student programs are, in many cases, complicated and time-consuming. In this article, we introduce a methodology with which thousands of programs can be analyzed in less than a second, for example, to search for the use of certain control structures or the application of recursion. For this purpose, we have developed a software that creates a structural representation for each programming solution in the form of a TGraph, which is inserted into a graph database using Neo4j. On this database, we can search for structural features by queries in the language Cypher. We have tested this methodology extensively for Java programs, measured its performance, and validated the results. Our software can also be applied to programs in other programming languages, such as Scratch. Additionally, we plan to make our software available to the community.",
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AU - Kögl, Adrian

AU - Hubwieser, Peter

AU - Talbot, Mike

AU - Krugel, Johannes

AU - Striewe, Michael

AU - Goedicke, Michael

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