SLE 2024 paper:
Efficient Demand Evaluation of Fixed-Point Attributes using Static Analysis

Idriss Riouak, Niklas Fors, Jesper Öqvist, Görel Hedin, Christoph Reichenbach

🏆 Distinguished Research Paper Award
DOI: 10.1145/3687997.3695644
T3A: Meta-languages
- The paper contributes to attribute-grammar style meta-languages by improving evaluation of fixed-point attributes.
T1B: Static Semantics
- Fixed-point attributes are commonly used to express static analyses (e.g., dataflow) in language definitions.
T5F: Performance
- Its main goal is to reduce evaluation cost by using static analysis to avoid unnecessary recomputation.

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