Design of a visual environment for programming by direct data manipulation
Bibliographic record
Abstract
The use of applications on computers, smartphones, and tablets has been considerably simplied thanks to interactive and dynamic graphical interfaces coupled with the mouse and touch screens. It is no longer necessary to be a computer specialist to use them. Paradoxically, the development of computer programs generally requires writing lines of code in a programming language whose syntax is particularly strict. This process poses many diculties for programmers. We propose an original tool in which arbitrary programs (Turing-complete) can be developed in a completely visual manner by direct manipulation of the data, without writing a line of code. The user can thus develop an algorithm by directly visualizing the result of actions taken on the data. A method for constructing iterations is associated with the tool. It proposes to create each part, including the loop body, in a non-linear manner under visual control of the state of the data. In addition, the tool supports the production of code that corresponds to the actions performed, where the language can be Python, C, or Java. In this article, we present the tool, the design choices, the problems solved, and the limits and contributions of the direct-data-manipulation approach.
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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 | 0.000 |
| 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 | 0.002 | 0.002 |
| 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 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".