遵循以下最佳实践的项目将能够自愿的自我认证,并显示他们已经实现了核心基础设施计划(OpenSSF)徽章。 显示详细资料
[](https://www.bestpractices.dev/projects/9424)
<a href="https://www.bestpractices.dev/projects/9424"><img src="https://www.bestpractices.dev/projects/9424/badge"></a>
TemporalScope: Scientifically driven Model-Agnostic Temporal Feature Importance Analysis with SHAP & partioning algorithms (supporting Pandas, Polars & Modin).
Repository on GitHub, which uses git. git is distributed.
警告:需要URL,但找不到URL。
Found all required security hardening headers.
The project is still in its early development stage. At this point, adding dynamic analysis tools such as fuzzing or runtime-based testing is not necessary, as the software has not yet reached the maturity level where such tools are required. The focus is currently on static analysis using tools like MyPy, Bandit, and Flake8 to catch potential issues early during development. Reference: Linux Foundation & OpenSSF's best practice documentation on Dynamic Code Analysis.
The project currently does not implement extensive dynamic analysis or fuzzing because it is in a pre-release phase. Once the software approaches a major production release, dynamic tools such as fuzzers and runtime assertion-based testing will be considered and incorporated into the CI/CD pipeline. For now, assertions are primarily used in unit tests to check runtime behavior during development. Reference: Linux Foundation & OpenSSF's best practice documentation on Dynamic Code Analysis.
后退