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Lazarus: Where Compilers Meet Education

Authors Rui Gonçalves , Pedro Rangel Henriques , José Carlos Ramalho

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OASIcs.SLATE.2026.19.pdf
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Subject Classification

ACM Subject Classification
  • Software and its engineering → Object oriented languages
  • Software and its engineering → Parsers
  • Software and its engineering → Compilers
  • Software and its engineering → Source code generation
  • Software and its engineering → Virtual machines
Keywords
  • Object-Oriented Programming
  • Compilation
  • SSA
  • Optimization
  • Virtual Machine
  • IDE

Metrics

Abstract

Lazarus is an intentionally compact platform featuring an optimizing compiler, a lightweight virtual machine and IDE integration. Its small size, lets students explore every compilation stage by experimenting with a compiler inspired by modern systems. At the core lies an incremental parser, that only re-parses the surrounding areas of the changed text in an IDE environment, and an SSA-based optimizer. The target machine is a register-based virtual machine, that mimics native architectures, and provides a debugger. This paper presents both the source language, and its register-based virtual machine, while discussing an often neglected feature in compiler design: the incremental parser.

Cite As Get BibTex

Rui Gonçalves, Pedro Rangel Henriques, and José Carlos Ramalho. Lazarus: Where Compilers Meet Education. In 15th Symposium on Languages, Applications and Technologies (SLATE 2026). Open Access Series in Informatics (OASIcs), Volume 144, pp. 19:1-19:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026) https://doi.org/10.4230/OASIcs.SLATE.2026.19

Author Details

Rui Gonçalves
  • ALGORITMI Research Centre / LASI, Dept. of Informatics, University of Minho, Braga, Portugal
Pedro Rangel Henriques
  • ALGORITMI Research Centre / LASI, Dept. of Informatics, University of Minho, Braga, Portugal
José Carlos Ramalho
  • ALGORITMI Research Centre / LASI, Dept. of Informatics, University of Minho, Braga, Portugal

Funding

This work has been supported by FCT - Fundação para a Ciência e Tecnologia within the R&D Unit Project Scope UID/00319/2025 - Centro ALGORITMI (ALGORITMI/UM) https://doi.org/10.54499/UID/00319/2025.

Acknowledgements

The authors would like to thank Neal Gafter and Eric Lippert (from the Roslyn team) for their valuable support, for answering numerous questions, and enabling some features presented in this work; and acknowledge the support and help of our families during this time.

Supplementary Materials

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