Anvil: A Tool for Visual Debugging of Rendering Pipelines

Kevin Napoli, Keith Bugeja, Sandro Spina, Mark Magro, Adrian De Barro

2022

Abstract

Debugging software can be challenging and numerous tools are used to aid in this task. Moreover, inspecting and debugging software of a certain nature such as those found in the subdomain of physically based rendering, where stochastic methods are often utilised, can be even more challenging. Traditional debugging in these cases is not ideal and in many cases not sufficient to help pinpoint certain issues, such as finding defects in the distribution of reflected rays in a ray-based rendering scenario. To address these issues we propose Anvil, a visual debugging tool that aims to seamlessly integrate within user applications, adhering to the what you don’t use, you don’t pay for C++ zero-overhead principle. Anvil is meant to be flexible, reusable, and extensible while adopting a low memory footprint. To achieve its goals, Anvil makes use of reflection-like techniques, adopts in situ analysis, and provides event hooks to communicate with the user application.

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Paper Citation


in Harvard Style

Napoli K., Bugeja K., Spina S., Magro M. and De Barro A. (2022). Anvil: A Tool for Visual Debugging of Rendering Pipelines. In Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 1: GRAPP; ISBN 978-989-758-555-5, SciTePress, pages 196-203. DOI: 10.5220/0010834200003124


in Bibtex Style

@conference{grapp22,
author={Kevin Napoli and Keith Bugeja and Sandro Spina and Mark Magro and Adrian De Barro},
title={Anvil: A Tool for Visual Debugging of Rendering Pipelines},
booktitle={Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 1: GRAPP},
year={2022},
pages={196-203},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010834200003124},
isbn={978-989-758-555-5},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 1: GRAPP
TI - Anvil: A Tool for Visual Debugging of Rendering Pipelines
SN - 978-989-758-555-5
AU - Napoli K.
AU - Bugeja K.
AU - Spina S.
AU - Magro M.
AU - De Barro A.
PY - 2022
SP - 196
EP - 203
DO - 10.5220/0010834200003124
PB - SciTePress