Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
A Tool for Generating Interactive Euler Diagrams
Authors: François Schwarzentruber
IJCAI 2016 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We describe a tool for generating Euler diagrams from a set of region connection calculus formulas. The generation is based on a variant of local search capturing default reasoning for improving aesthetic appearance of Euler diagrams. We also describe an optimization for diagrams to be interactive: the user can modify the diagram with the mouse while formulas are still satisfied. Our second contribution is a smoother interaction (it is measured by two factors: the constraint satisfaction and the fact that the new obtained diagram is close to the initial one). |
| Researcher Affiliation | Academia | Franc ois Schwarzentruber ENS Rennes / IRISA, Rennes, France EMAIL |
| Pseudocode | No | The paper describes algorithms and rules textually, such as the rules for saturating the graph, but it does not include a structured pseudocode or algorithm block. |
| Open Source Code | Yes | We propose an implementation written in Javascript2 where the aesthetic is taken into account by two aspects: default reasoning and interactive drawings. 2http://people.irisa.fr/Francois.Schwarzentruber/ constrainteddrawing/ |
| Open Datasets | No | The paper describes a tool for generating Euler diagrams from logical formulas and does not mention the use of any public or open datasets for training or evaluation. |
| Dataset Splits | No | The paper does not discuss dataset splits, as it focuses on generating diagrams from logical formulas rather than training models on datasets. |
| Hardware Specification | No | The paper describes a Javascript implementation but provides no specific details about the hardware (e.g., CPU, GPU models, memory) used for development or demonstration. |
| Software Dependencies | No | The paper states the implementation is 'written in Javascript' but does not specify any version numbers for Javascript or any other software dependencies or libraries. |
| Experiment Setup | No | The paper describes the underlying algorithms and logical rules, but it does not provide specific experimental setup details such as hyperparameter values, training configurations, or system-level settings. |