MLCatchUp: Automated Update of Deprecated Machine-Learning APIs in Python
| Autor: | Ferdian Thung, Stefanus Agus Haryono, David Lo, Julia Lawall, Lingxiao Jiang |
|---|---|
| Přispěvatelé: | Singapore Management University (SIS), Singapore Management University, Well Honed Infrastructure Software for Programming Environments and Runtimes ( Whisper), Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-LIP6, Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), This research is also supported by the Singapore National Research Foundation (award number: NRF2016-NRF-ANR003), ANR-16-CE25-0012,ITrans,Inférence automatique de règles de transformation pour le portage des logiciels d'infrastructure patrimoniaux(2016), Well Honed Infrastructure Software for Programming Environments and Runtimes (Whisper), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria) |
| Rok vydání: | 2021 |
| Předmět: |
Computer science
Process (engineering) business.industry A domain Program transformation 020207 software engineering Deprecated API [INFO.INFO-SE]Computer Science [cs]/Software Engineering [cs.SE] 02 engineering and technology Python (programming language) Machine learning computer.software_genre Program Transformation Deprecated Digital subscriber line 0202 electrical engineering electronic engineering information engineering Code (cryptography) Artificial intelligence Automatic Update business computer Python computer.programming_language |
| Zdroj: | ICSME ICSME 2021-37th IEEE International Conference on Software Maintenance and Evolution ICSME 2021-37th IEEE International Conference on Software Maintenance and Evolution, Sep 2021, Luxembourg City / Virtual, Luxembourg. ⟨10.1109/ICSME52107.2021.00061⟩ |
| Popis: | Tool Paper; International audience; Machine learning (ML) libraries are gaining vast popularity, especially in the Python programming language. Using the latest version of such libraries is recommended to ensure the best performance and security. When migrating to the latest version of a machine learning library, usages of deprecated APIs need to be updated, which is a time-consuming process. In this paper, we propose MLCatchUp, an automated API usage update tool for deprecated APIs of popular ML libraries written in Python. MLCatchUp automatically infers the required transformation to migrate usages of deprecated API through the differences between the deprecated and updated API signatures. MLCatchUp offers a readable transformation rule in the form of a domain specific language (DSL). We evaluate MLCatchUp using a dataset of 267 real-world Python code containing 551 usages of 68 distinct deprecated APIs, where MLCatchUp achieves 90.7% accuracy. A video demonstration of MLCatchUp is available at https://youtu.be/5NjOPNt5iaA. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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