Tooling

This page contains links to all relevant tooling created as part of the project (none so far) as well as external code tools for which applicability needs to be verified.

While I currently have no plans to use machine learning rather than some old-fashioned handcrafted algorithm for patch classification, this might change if deemed useful.

External projects

PatchNet: A Tool for Deep Patch Classification

This work proposes PatchNet, an automated tool based on hierarchical deep learning for classifying patches by extracting features from commit messages and code changes. PatchNet contains a deep hierarchical structure that mirrors the hierarchical and sequential structure of a code change, differentiating it from the existing deep learning models on source code. PatchNet provides several options allowing users to select parameters for the training process. The tool has been validated in the context of automatic identification of stable-relevant patches in the Linux kernel and is potentially applicable to auto- mate other software engineering tasks that can be formulated as patch classification problems. A video demonstrating PatchNet is available at https://goo.gl/CZjG6X. The PatchNet implementation is available at https://github.com/hvdthong/PatchNetTool.