sdc-scissor

A tool for predicting unsafe road scenarios for self-driving cars in BeamNG.tech.

https://github.com/christianbirchler-org/sdc-scissor

Science Score: 67.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
    Found CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
    Found 22 DOI reference(s) in README
  • Academic publication links
    Links to: zenodo.org
  • Academic email domains
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (5.3%) to scientific vocabulary

Keywords

beamng regression-test-selection self-driving-cars simulation-environment testing-tool
Last synced: 6 months ago · JSON representation ·

Repository

A tool for predicting unsafe road scenarios for self-driving cars in BeamNG.tech.

Basic Info
  • Host: GitHub
  • Owner: christianbirchler-org
  • License: gpl-3.0
  • Language: Python
  • Default Branch: main
  • Homepage:
  • Size: 45.7 MB
Statistics
  • Stars: 25
  • Watchers: 5
  • Forks: 3
  • Open Issues: 25
  • Releases: 17
Topics
beamng regression-test-selection self-driving-cars simulation-environment testing-tool
Created almost 5 years ago · Last pushed over 1 year ago
Metadata Files
Readme Contributing License Code of conduct Citation

README.md

SDC-Scissor

```{code-block} text


/\ \ /\ _\ /\ _\ /\ _\ _ \ \,\L_\ \ \/\ \ \ \/_\ \ \,\L_\ ___ /_\ ____ ____ ___ _ __ \/_ \ \ \ \ \ \ \// ____\/__ \ /'\/\ \ /',\ /',\ / _\/\'\ /\ \L\ \ \ _\ \ \ \L\ \/_\ /\ \L\ \/\ _/\ \ \/_, `\/_, \/\ \L\ \ \ \/ \_\ _/\ _/\/__/ \ `_\ _\ _\/_/\/_/\ _/\ _\ \/__/\// \// \//\// \/_/\// \// \// \//

``` License: GPL v3 Conventional Commits GitHub issues GitHub forks GitHub stars PyPI DOI

A Tool for Cost-effective Simulation-based Test Selection in Self-driving Cars Software

SDC-Scissor is a tool that let you test self-driving cars more efficiently in simulation. It uses a machine-learning approach to select only relevant test scenarios so that the testing process is faster. Furthermore, the selected tests are diverse and try to challenge the car with corner cases.

Furthermore, this repository contains also code for test multi-objective test case prioritization with an evolutionary genetic search algorithm. If you are interested in prioritizing test cases, then you should read the dedicated README.md for this. If you use the prioritization technique then also cite the papers from the reference section!

Support

We use GitHub Discussions as a community platform. You can ask questions and get support there from the community. Furthermore, new features and releases will be discussed and announced there.

Documentation

For the documentation follow the link: sdc-scissor.readthedocs.io

License

```{code-block} text SDC-Scissor tool for cost-effective simulation-based test selection in self-driving cars software. Copyright (C) 2024 Christian Birchler

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program. If not, see https://www.gnu.org/licenses/. ```

The software we developed is distributed under GNU GPL license. See the LICENSE.md file.

References

If you use this tool in your research, please cite the following papers:

  • Christian Birchler, Cyrill Rohrbach, Hyeongkyun Kim, Alessio Gambi, Tianhai Liu, Jens Horneber, Timo Kehrer, Sebastiano Panichella, "TEASER: Simulation-based CAN Bus Regression Testing for Self-driving Cars Software," In 38th IEEE/ACM International Conference on Automated Software Engineering (ASE), 2023, DOI: to appear.

    • Preprint
    • TEASER Tool Documentation
    • Submitted GitHub Release {code-block} bibtex @article{Birchler2023Teaser, author = {Christian Birchler and Cyrill Rohrbach and Hyeongkyun Kim and Alessio Gambi and Tianhai Liu and Jens Horneber and Timo Kehrer and Sebastiano Panichella}, title = {{TEASER}: Simulation-based CAN Bus Regression Testing for Self-driving Cars Software}, booktitle = {{IEEE/ACM} International Conference on Automated Software Engineering}, year = {2023}, eprint = {2307.03279}, doi = {10.48550/arXiv.2307.03279}, }
  • Christian Birchler, Nicolas Ganz, Sajad Khatiri, Alessio Gambi, and Sebastiano Panichella, "Cost-effective Simulation-based Test Selection in Self-driving Cars Software with SDC-Scissor," In 2022 IEEE 29th International Conference on Software Analysis, Evolution and Reengineering (SANER), pp. 164-168, DOI: 10.1109/SANER53432.2022.00030.

    • IEEE Xplore
    • Preprint
    • GitHub {code-block} bibtex @inproceedings{Birchler2022Cost1, author={Birchler, Christian and Ganz, Nicolas and Khatiri, Sajad and Gambi, Alessio, and Panichella, Sebastiano}, booktitle={2022 IEEE 29th International Conference on Software Analysis, Evolution and Reengineering (SANER)}, title={Cost-effective Simulationbased Test Selection in Self-driving Cars Software with SDC-Scissor}, year={2022}, doi={10.1109/SANER53432.2022.00030} }
  • Christian Birchler, Nicolas Ganz, Sajad Khatiri, Alessio Gambi, and Sebastiano Panichella, "Cost-effective Simulation-based Test Selection in Self-driving Cars Software," Science of Computer Programming (SCP), DOI: 10.1016/j.scico.2023.102926, 2023.

    • Elsevier {code-block} bibtex @article{Birchler2022Cost2, author = {Christian Birchler and Nicolas Ganz and Sajad Khatiri and Alessio Gambi and Sebastiano Panichella}, title = {Cost-effective Simulation-based Test Selection in Self-driving Cars Software}, journal = {Science of Computer Programming (SCP)}, volume = {226}, year = {2023}, doi = {10.1016/j.scico.2023.102926}, pages = {102926}, year = {2023}, issn = {0167-6423}, }
  • Christian Birchler, Sajad Khatiri, Bill Bosshard, Alessio Gambi, and Sebastiano Panichella, "Machine Learning-based Test Selection for Simulation-based Testing of Self-driving Cars Software," Empirical Software Engineering (EMSE), DOI: 10.1007/s10664-023-10286-y, 2023.

    • Preprint {code-block} bibtex @article{Birchler2022Machine, author = {Christian Birchler and Sajad Khatiri and Bill Bosshard and Alessio Gambi and Sebastiano Panichella}, title = {Machine Learning-based Test Selection for Simulation-based Testing of Self-driving Cars Software}, journal = {Empirical Software Engineering (EMSE)}, year = {2022}, doi = {to appear}, eprinttype = {arXiv}, eprint = {2212.04769} }
  • Christian Birchler, Sajad Khatiri, Pouria Derakhshanfar, Sebastiano Panichella, and Annibale Panichella, "Single and Multi-objective Test Cases Prioritization for Self-driving Cars in Virtual Environments," ACM Transactions on Software Engineering and Methodology (TOSEM), DOI: 10.1145/3533818, 2023.

    • ACM Digital Library
    • Preprint {code-block} bibtex @article{Birchler2022Single, author={Birchler, Christian and Khatiri, Sajad and Derakhshanfar, Pouria and Panichella, Sebastiano and Panichella, Annibale}, title={Single and Multi-objective Test Cases Prioritization for Self-driving Cars in Virtual Environments}, year={2022}, publisher={Association for Computing Machinery}, journal={ACM Transactions on Software Engineering and Methodology (TOSEM)}, doi={10.1145/3533818} }

Contacts

  • Christian Birchler
    • Zurich University of Applied Sciences (ZHAW), Switzerland - birc@zhaw.ch
  • Nicolas Ganz
    • Zurich University of Applied Sciences (ZHAW), Switzerland - gann@zhaw.ch
  • Sajad Khatiri
    • Zurich University of Applied Sciences (ZHAW), Switzerland - mazr@zhaw.ch
  • Dr. Alessio Gambi
    • IMC University Of Applied Sciences Krems, Austria - alessio.gambi@fh-krems.ac.at
  • Dr. Sebastiano Panichella
    • Zurich University of Applied Sciences (ZHAW), Switzerland - panc@zhaw.ch

Owner

  • Name: ChristianBirchler.org
  • Login: christianbirchler-org
  • Kind: organization
  • Location: Switzerland

Software Engineering Research Repositories

Citation (CITATION.cff)

# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!

cff-version: 1.2.0
title: SDC-Scissor
message: >-
  A Tool for Cost-effective Simulation-based Test Selection
  in Self-driving Cars Software
type: software
authors:
  - given-names: Christian
    family-names: Birchler
    email: birc@zhaw.ch
    affiliation: Zurich University of Applied Sciences
    orcid: 'https://orcid.org/0000-0003-3987-0276'
  - given-names: Nicolas
    family-names: Ganz
    email: gann@zhaw.ch
    affiliation: Zurich University of Applied Sciences
    orcid: 'https://orcid.org/0000-0002-4165-0275'
  - given-names: Sajad
    family-names: Khatiri
    email: mazr@zhaw.ch
    affiliation: Zurich University of Applied Sciences
    orcid: 'https://orcid.org/0000-0003-0354-9747'
  - given-names: Alessio
    family-names: Gambi
    email: alessio.gambi@fh-krems.ac.at
    orcid: 'https://orcid.org/0000-0002-0132-6497'
    affiliation: University of Passau
  - given-names: Sebastiano
    family-names: Panichella
    email: panc@zhaw.ch
    affiliation: Zurich University of Applied Sciences
    orcid: 'https://orcid.org/0000-0003-4120-626X'
identifiers:
  - type: doi
    value: 10.1016/j.scico.2023.102926
    description: >-
      Original Software Publication at the Science of
      Computer Programming journal
  - type: doi
    value: 10.1109/SANER53432.2022.00030
    description: Tool Demo Paper at SANER 2022
repository-code: 'https://github.com/ChristianBirchler/sdc-scissor'
url: 'https://sdc-scissor.readthedocs.io/'
license: GPL-3.0

GitHub Events

Total
  • Watch event: 3
  • Fork event: 1
Last Year
  • Watch event: 3
  • Fork event: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 84
  • Total pull requests: 15
  • Average time to close issues: 2 months
  • Average time to close pull requests: 3 days
  • Total issue authors: 4
  • Total pull request authors: 6
  • Average comments per issue: 0.57
  • Average comments per pull request: 1.47
  • Merged pull requests: 13
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • ChristianBirchler (77)
  • tanzilkm (3)
  • AbdelrahmanElsaidElsawy (3)
  • neelofarhassan (1)
Pull Request Authors
  • ChristianBirchler (5)
  • tanzilkm (5)
  • spanichella (2)
  • dgumenyuk (1)
  • andrius-k (1)
  • ThunderKey (1)
Top Labels
Issue Labels
enhancement (51) documentation (12) bug (10) question (1)
Pull Request Labels
enhancement (2)