Flix: A Design for Language-Integrated Datalog
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We present a comprehensive overview of the Datalog facilities in the Flix programming language. We show how programmers can write functions implemented as Datalog programs and we demonstrate how to build modular and reusable families of Datalog programs using first-class Datalog program values, rho abstraction, parametric polymorphism, and type classes. We describe several features that improve the ergonomics, flexibility, and expressive power of Datalog programming in Flix, including the inject and query program constructs, head and guard expressions, functional predicates, lattice semantics, and more. We illustrate Datalog programming in Flix with several applications, including implementations of Ullman's algorithm to stratify Datalog programs, the Ford-Fulkerson algorithm for maximum flow, and the IFDS and IDE algorithms for context-sensitive program analysis. The implementations of IFDS and IDE fulfill a long-term goal: to have fully modular, polymorphic, typed, and declarative formulations of these algorithms that can be instantiated with any abstract domain.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it