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

Adrian Koegl, Peter Hubwieser, Mike Talbot, Johannes Krugel, Michael Striewe, Michael Goedicke

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

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.

Original languageEnglish
Title of host publicationProceedings of the 2022 IEEE Global Engineering Education Conference, EDUCON 2022
EditorsMohammed Jemni, Ilhem Kallel, Abdeljalil Akkari
PublisherIEEE Computer Society
Pages24-30
Number of pages7
ISBN (Electronic)9781665444347
DOIs
StatePublished - 2022
Event13th IEEE Global Engineering Education Conference, EDUCON 2022 - Tunis, Tunisia
Duration: 28 Mar 202231 Mar 2022

Publication series

NameIEEE Global Engineering Education Conference, EDUCON
Volume2022-March
ISSN (Print)2165-9559
ISSN (Electronic)2165-9567

Conference

Conference13th IEEE Global Engineering Education Conference, EDUCON 2022
Country/TerritoryTunisia
CityTunis
Period28/03/2231/03/22

Keywords

  • Automated assessment systems
  • graph database
  • introductory lectures
  • large-scale education
  • learning analytics
  • programming assignments
  • source code representation
  • structural code analysis

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