Integrating design synthesis and assembly of structured objects in a visual design language
Bibliographic record
Abstract
Computer Aided Design systems provide tools for building and manipulating models of solid objects. Some also provide access to programming languages so that parametrised designs can be expressed. There is a sharp distinction, therefore, between building models, a concrete graphical editing activity, and programming, an abstract, textual, algorithm-construction activity. The recently proposed Language for Structured Design (LSD) was motivated by a desire to combine the design and programming activities in one language. LSD achieves this by extending a visual logic programming language to incorporate the notions of solids and operations on solids. Here we investigate another aspect of the LSD approach; namely, that by using visual logic programming as the engine to drive the parametrised assembly of objects, we also gain the powerful symbolic problem-solving capability that is the forte of logic programming languages. This allows the designer/programmer to work at a higher level, giving declarative specifications of a design in order to obtain the design descriptions. Hence LSD integrates problem solving, design synthesis, and prototype assembly in a single homogeneous programming/design environment. We demonstrate this specification-to-final-assembly capability using the masterkeying problem for designing systems of locks and keys.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".