3 Metrics for ML Pipelines Code Smells
- Scattered Use of ML Library. This smell is related to the previous one because it also refers to the use of ML libraries. ...
- Dispensable Dependency. ...
- Abstraction Debt.
Dec 11, 2023 · This work in progress proposes initial metrics to measure the presence of code smells in ML pipelines. These metrics reflect good software engineering ...
In this work, we perform a first evaluation of a set of metrics, proposed in previous research, for measuring the presence of code smells related to ...
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In this work, we perform a first evaluation of a set of metrics, proposed in previous research, for measuring the presence of code smells related to ...
To address this problem, this work in progress proposes initial metrics to measure the presence of code smells in ML pipelines. These metrics reflect good ...
Metrics for Code Smells of ML Pipelines. https://doi.org/10.1007/978-3-031-49269-3_1 ·. Journal: Product-Focused Software Process Improvement Lecture Notes ...
For the purpose of this study, the author was mostly interested in broken conventions, warnings, and refactoring suggestions which are in essence code smells.
Aug 24, 2024 · Firstly, finding the properties and characteristics of AITD issues can improve the investigation of their presence. A recent study conducted ...
Our paper proposes and identifies a list of 22 machine learning-specific code smells collected from various sources.
To address this problem, this work in progress proposes initial metrics to measure the presence of code smells in ML pipelines. These metrics reflect good ...