Adaptive Semantics for Generic Latex Expressions in the Context of Educational Resources

January 29th, 2024

This thesis aims at developing a pipeline for automatic translation of generic latex expression into domain specific, processable, languages.

Thesis Type
  • Bachelor
  • Master
David Korets'kyy
Presentation room
Seminar room I5 6202
Stefan Decker
Laurenz Neumann
Maximilian Kißgen

In many domains of computer science, such as database theory, notations encompass a variety of mathematical terms, for which many use LaTeX, a popular markup language for mathematical notations.
However, as a language purely for markup, its semantics cannot be directly processed within specific domains, for instance, relational algebra. This presents challenges for LaTeX in education. Here, students often cannot use the language in automatically graded exercises but need to instead use specifically defined languages that can be programmatically processed.
This thesis project aims to address this challenge by developing a pipeline to translate well-defined subsets of LaTeX expressions into domain-specific, processable algebras, enabling better comprehension and enhancing assignments with automatic assessment. To assess whether student learning experience is improved, the pipeline should be evaluated via a user survey.

Goals & Objectives:

  • Formulating the theoretical background of adapting latex expressions into domain specific algebras
  • Exploring and adapting state-of-the-art approaches for parser generation and LaTeX translation
  • Developing a parser and modular framework to translate LaTeX-expressions into domain-specific representations via Python
  • Evaluating the impact of LaTeX statements for automated assessments on student learning experience


Validity of the algebraic statements must be ensured, this includes ambiguities in LaTeX notations (e.g. “->” versus “\rightarrow”, parentheses, etc.). In addition, the framework needs to maintain its modularity, meaning that users have to be able to define their own translation rules without breaking the system.

  • Proficiency in Python, LaTeX
  • Basic knowledge about parsers and formal grammars
  • Nice to have: proficiency in ANTLR & jupyter notebooks, knowledge about compilers