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Just-in-Time Software Defect Prediction Via Bi-Modal Change Representation Learning
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Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/bltj.2229openalex-snapshot
Predicting risk of software changes
inferredcites →https://doi.org/10.1007/s10664-021-10083-5openalex-snapshot
A fine-grained data set and analysis of tangling in bug fixing commits
inferredcites →https://doi.org/10.1007/s10664-024-10591-0openalex-snapshot
Bridging expert knowledge with deep learning techniques for just-in-time defect prediction
inferredcites →https://doi.org/10.1007/s42979-021-00566-zopenalex-snapshot
Commit2Vec: Learning Distributed Representations of Code Changes
inferredcites →https://doi.org/10.1016/j.infsof.2023.107393openalex-snapshot
Multi-grained contextual code representation learning for commit message generation
inferredcites →https://doi.org/10.1016/j.jss.2024.112014openalex-snapshot
Code-centric learning-based just-in-time vulnerability detection
inferredcites →https://doi.org/10.1016/j.knosys.2022.108852openalex-snapshot
Just-in-time defect prediction based on AST change embedding
inferredcites →https://doi.org/10.1016/j.neucom.2021.05.039openalex-snapshot
CoreGen: Contextualized Code Representation Learning for Commit Message Generation
inferredcites →https://doi.org/10.1109/iccv.2017.74openalex-snapshot
Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization
inferredcites →https://doi.org/10.1109/icsme.2018.00046openalex-snapshot
Are Bug Reports Enough for Text Retrieval-Based Bug Localization?
inferredcites →https://doi.org/10.1109/icsme58846.2023.00028openalex-snapshot
CCBERT: Self-Supervised Code Change Representation Learning
inferredcites →https://doi.org/10.1109/msr52588.2021.00049openalex-snapshot
JITLine: A Simpler, Better, Faster, Finer-grained Just-In-Time Defect Prediction
inferredcites →https://doi.org/10.1109/msr59073.2023.00072openalex-snapshot
Boosting Just-in-Time Defect Prediction with Specific Features of C/C++ Programming Languages in Code Changes
inferredcites →https://doi.org/10.1109/qrs.2015.14openalex-snapshot
Deep Learning for Just-in-Time Defect Prediction
inferredcites →https://doi.org/10.1109/saner56733.2023.00038openalex-snapshot
Slice-Based Code Change Representation Learning
inferredcites →https://doi.org/10.1109/tse.2017.2693980openalex-snapshot
Are Fix-Inducing Changes a Moving Target? A Longitudinal Case Study of Just-In-Time Defect Prediction
inferredcites →https://doi.org/10.1109/tse.2018.2876256openalex-snapshot
How Well Do Change Sequences Predict Defects? Sequence Learning from Software Changes
inferredcites →https://doi.org/10.1109/tse.2020.2978819openalex-snapshot
Just-In-Time Defect Identification and Localization: A Two-Phase Framework
inferredcites →https://doi.org/10.1142/s0218194023500493openalex-snapshot
Context-Encoded Code Change Representation for Automated Commit Message Generation
inferredcites →https://doi.org/10.1145/3180155.3182514openalex-snapshot
Are fix-inducing changes a moving target?
inferredcites →https://doi.org/10.1145/3290353openalex-snapshot
code2vec: learning distributed representations of code
inferredcites →https://doi.org/10.1145/3338906.3338962openalex-snapshot
Exploring and exploiting the correlations between bug-inducing and bug-fixing commits
inferredcites →https://doi.org/10.1145/3428283openalex-snapshot
A structural model for contextual code changes
inferredcites →https://doi.org/10.1145/3460319.3464819openalex-snapshot
Deep just-in-time defect prediction: how far are we?
inferredcites →https://doi.org/10.1145/3472674.3473979openalex-snapshot
Unsupervised learning of general-purpose embeddings for code changes
inferredcites →https://doi.org/10.1145/3508479openalex-snapshot
Just-In-Time Defect Prediction on JavaScript Projects: A Replication Study
inferredcites →https://doi.org/10.1145/3540250.3549165openalex-snapshot
The best of both worlds: integrating semantic features with expert features for defect prediction and localization
inferredcites →https://doi.org/10.1145/3567550openalex-snapshot
A Systematic Survey of Just-in-Time Software Defect Prediction
inferredcites →https://doi.org/10.1145/3611643.3616339openalex-snapshot
CCT5: A Code-Change-Oriented Pre-trained Model
inferredcites →https://doi.org/10.1609/aaai.v35i15.17606openalex-snapshot
Copy That! Editing Sequences by Copying Spans
inferredcites →https://doi.org/10.26153/tsw/43665openalex-snapshot
Multi-timescale Representation Learning in LSTM Language Models
inferredcites →https://doi.org/10.4230/lipics.itp.2023.19openalex-snapshot
Exploiting Generative AI to Scale up Intelligent Tutoring Systems
inferredcites →https://doi.org/10.48550/arxiv.1810.13337openalex-snapshot
Learning to Represent Edits
inferredcites →https://doi.org/10.48550/arxiv.2003.05620openalex-snapshot
CC2Vec: Distributed Representations of Code Changes
inferredcites →https://doi.org/10.48550/arxiv.2101.12087openalex-snapshot
Learning Structural Edits via Incremental Tree Transformations
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