Jeff Smits

dblp:117/1776 · DBLP profile ↗
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4ranked-venue papers
3as first author
2since 2021 · last 2024
0000-0002-8053-8868ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 4 · 3 first-author · 2 since 2021Artificial intelligence and machine learning · 1 · 1 since 2021
YearPublicationVenuePosition
2024 A Multi-Stage Proof Logging Framework to Certify the Correctness of CP Solvers
Maarten Flippo, Konstantin Sidorov, Imko Marijnissen, Jeff Smits, Emir Demirovic
CP4
2022 Optimising First-Class Pattern Matching
abstract
Pattern matching is a high-level notation for programs to analyse the shape of data, and can be optimised to efficient low-level instructions. The Stratego language uses first-class pattern matching, a powerful form of pattern matching that traditional optimisation techniques do not apply to directly.
Jeff Smits, Toine Hartman, Jesper Cockx
SLE1
2020 Gradually typing strategies
abstract
The Stratego language supports program transformation by means of term rewriting with programmable rewriting strategies. Stratego's traversal primitives support concise definition of generic tree traversals. Stratego is a dynamically typed language because its features cannot be captured fully by a static type system. While dynamic typing makes for a flexible programming model, it also leads to unintended type errors, code that is harder to maintain, and missed opportunities for optimization.
Jeff Smits, Eelco Visser
SLE1
2017 FlowSpec: declarative dataflow analysis specification
abstract
We present FlowSpec, a declarative specification language for the domain of dataflow analysis. FlowSpec has declarative support for the specification of control flow graphs of programming languages, and dataflow analyses on these control flow graphs. We define the formal semantics of FlowSpec, which is rooted in Monotone Frameworks. We also discuss a prototype implementation of the language, built in the Spoofax Language Workbench. Finally, we evaluate the expressiveness and conciseness of the language with two case studies. These case studies are analyses for Green-Marl, an industrial, domain-specific language for graph processing. The first case study is a classical dataflow analysis, scaled to this full language. The second case study is a domain-specific analysis of Green-Marl.
Jeff Smits, Eelco Visser
SLE1