scw_2026_indicators_resources

Introduction

This repository contains the source code and data necessary to reproduce the results of the use cases of the paper "Influence of Environmental Indicators Aggregation Methods for Eco-designing Integrated Circuits" published in the Proceedings of the 23rd ACM International Conference on Computing Frontiers (CF26) (https://doi.org/10.1145/3801488.3806643).

In particular, the repository contains :

• Data to generate impact models with Appabuild in scw26/conf and scw26/datasets.
• Python scripts to run impact models and compute environmental scores for the three case studies of the paper in scw26/scripts/save_*.py.
• Environmental scores obtained for the three case studies of the paper in scw26/scripts/results/*.csv.
• Python scripts to plot the figures of the paper from the raw environmental data in scw26/scripts/plot_*.py.
• Figures of the environmental scores of the three case studies used in the paper in scw26/scripts/results/*.svg.

Licensing

Please refer to the LICENCE.md document for the licencing rights granted for the content of this repository.

Warning: for some datasets in scw26/datasets, other licences could apply. They are indicated in the header of the files, please read it carefully.

Citation

For any use of the data, scripts or results in this repo, please cite:

Abernot, M., Lemaire, R., & Péralta, M. (2026). Influence of Environmental Indicators Aggregation Methods for Eco-designing Integrated Circuits. In Proceedings of the 23rd ACM International Conference on Computing Frontiers (CF Companion ’26 ). 

Setup environment

Define project directory with the extracted data and move in the directory. Attention: do not use ~/ in the path.

export SCW26_DATA_DIR=path_to_scw26/scw26
cd $SCW26_DATA_DIR

Install necessary packages in your working directory. It is recommended to use python 3.11 virtualenv to limit dependency conflicts.

pip install -r requirements.txt

If necessary, a full documentation of Appa LCA (including Appabuild and Apparun) is available in https://appalca.github.io/home/home.html.

Generate impact models with Appabuild

An Ecoinvent licence access is required to generate impact models. In the paper, Ecoinvent 3.11 cutoff was used.

Declare your Ecoinvent access with:

export BW_USER=username
export BW_PASS=pathword

Run Appabuild to generate impact models with:

• The Appa configuration file as first argument
• the impact model configuration file as second argument.

For the paper, we generated 3 impact models:

appabuild lca build conf/appalca_conf.yaml conf/ic_model_conf.yaml
appabuild lca build conf/appalca_conf_pkg.yaml conf/ic_model_conf_pkg.yaml
appabuild lca build conf/appalca_conf_no_pkg.yaml conf/ic_model_conf_no_pkg.yaml

/!\ There is a syntax error to be fixed in the generated impact models. In ic_model.yaml and ic_model_no_pkg.yaml, replace all occurence of -die_defect_density with -1*die_defect_density.

Compute environmental scores with Apparun

Impact models generated with Appabuild are required to compute environmental scores.

For the three case studies of the paper, final environmental scores are already computed and available in scw26/scripts/results/*.csv.

It is possible to re-configure environment models with other integrated circuit specifications and to compute new environmental scores using python scripts scripts/save_*.py. For example,

py $SCW26_DATA_DIR/scripts/save_arch_usecase_node.py

Plot figures

Figures of the paper can be plot for the three case studies using environmental scores available in scw26/scripts/results/*.csv.

To do so, run python scripts scripts/plot_*.py. For example,

py $SCW26_DATA_DIR/scripts/plot_arch_usecase_node.py