Analyzing the Evolution and Impact of Code Clones in Deep Learning Frameworks

Deep learning frameworks exhibit distinct long-term trends in code clone evolution, with varying characteristics in terms of cloned code size, bug-proneness, and community involvement. Short-term within-release code cloning practices also impact the long-term clone trends. Cross-framework code clones reveal functional and architectural adaptations across deep learning frameworks.