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Exploring the Impact of Code Clones on Deep Learning Software
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/3-540-45672-4_31openalex-snapshot
Refactoring: Improving the Design of Existing Code
inferredcites →https://doi.org/10.1007/3-540-47764-0_3openalex-snapshot
Using Slicing to Identify Duplication in Source Code
inferredcites →https://doi.org/10.1007/978-3-030-59410-7_40openalex-snapshot
An Empirical Study on Bugs Inside TensorFlow
inferredcites →https://doi.org/10.1007/s10664-008-9076-6openalex-snapshot
“Cloning considered harmful” considered harmful: patterns of cloning in software
inferredcites →https://doi.org/10.1007/s10664-021-10099-xopenalex-snapshot
Clones in deep learning code: what, where, and why?
inferredcites →https://doi.org/10.1007/s11432-020-3182-1openalex-snapshot
Reveal training performance mystery between TensorFlow and PyTorch in the single GPU environment
inferredcites →https://doi.org/10.1016/j.infsof.2013.01.008openalex-snapshot
Software clone detection: A systematic review
inferredcites →https://doi.org/10.1016/j.infsof.2017.09.011openalex-snapshot
Understanding metric-based detectable smells in Python software: A comparative study
inferredcites →https://doi.org/10.1016/j.infsof.2021.106566openalex-snapshot
Augmenting commit classification by using fine-grained source code changes and a pre-trained deep neural language model
inferredcites →https://doi.org/10.1016/j.jcp.2018.10.045openalex-snapshot
Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations
inferredcites →https://doi.org/10.1016/j.jss.2017.11.039openalex-snapshot
Scalable code clone detection and search based on adaptive prefix filtering
inferredcites →https://doi.org/10.1016/j.scico.2009.02.007openalex-snapshot
Comparison and evaluation of code clone detection techniques and tools: A qualitative approach
inferredcites →https://doi.org/10.1109/csmr.2007.26openalex-snapshot
How Clones are Maintained: An Empirical Study
inferredcites →https://doi.org/10.1109/cvpr.2017.106openalex-snapshot
Feature Pyramid Networks for Object Detection
inferredcites →https://doi.org/10.1109/ecai33499.2014openalex-snapshot
Proceedings of the 2014 6th International Conference on Electronics, Computers and Artificial Intelligence (ECAI)
inferredcites →https://doi.org/10.1109/ecai52376.2021.9515098openalex-snapshot
Comparison of Tensorflow and PyTorch in Convolutional Neural Network - based Applications
inferredcites →https://doi.org/10.1109/icpc.2008.41openalex-snapshot
NICAD: Accurate Detection of Near-Miss Intentional Clones Using Flexible Pretty-Printing and Code Normalization
inferredcites →https://doi.org/10.1109/icpc.2019.00022openalex-snapshot
Comparing Bug Replication in Regular and Micro Code Clones
inferredcites →https://doi.org/10.1109/icse.2007.30openalex-snapshot
DECKARD: Scalable and Accurate Tree-Based Detection of Code Clones
inferredcites →https://doi.org/10.1109/icse.2007.97openalex-snapshot
Very-Large Scale Code Clone Analysis and Visualization of Open Source Programs Using Distributed CCFinder: D-CCFinder
inferredcites →https://doi.org/10.1109/icse43902.2021.00068openalex-snapshot
An Empirical Study on Deployment Faults of Deep Learning Based Mobile Applications
inferredcites →https://doi.org/10.1109/icsm.2008.4658071openalex-snapshot
Assessing the effect of clones on changeability
inferredcites →https://doi.org/10.1109/icsm.2015.7332455openalex-snapshot
A comparative study on the bug-proneness of different types of code clones
inferredcites →https://doi.org/10.1109/icsme.2014.54openalex-snapshot
Evaluating Modern Clone Detection Tools
inferredcites →https://doi.org/10.1109/icsme.2017.46openalex-snapshot
CCLearner: A Deep Learning-Based Clone Detection Approach
inferredcites →https://doi.org/10.1109/icsme.2019.00026openalex-snapshot
Investigating Context Adaptation Bugs in Code Clones
inferredcites →https://doi.org/10.1109/icsme52107.2021.00001openalex-snapshot
Proceedings 2021 IEEE International Conference on Software Maintenance and Evolution
inferredcites →https://doi.org/10.1109/ipdpsw.2019.00138openalex-snapshot
Neural Network Frameworks. Comparison on Public Transportation Prediction
inferredcites →https://doi.org/10.1109/iwsc.2017.7880507openalex-snapshot
Does cloned code increase maintenance effort?
inferredcites →https://doi.org/10.1109/mc.2006.246openalex-snapshot
Three Public Enemies: Cut, Copy, and Paste
inferredcites →https://doi.org/10.1109/saner.2016.78openalex-snapshot
Bug Replication in Code Clones: An Empirical Study
inferredcites →https://doi.org/10.1109/saner.2019.8667993openalex-snapshot
A Comparative Study of Software Bugs in Micro-clones and Regular Code Clones
inferredcites →https://doi.org/10.1109/saner48275.2020.9054846openalex-snapshot
Associating Code Clones with Association Rules for Change Impact Analysis
inferredcites →https://doi.org/10.1109/scam.2014.13openalex-snapshot
A Change-Type Based Empirical Study on the Stability of Cloned Code
inferredcites →https://doi.org/10.1109/scam.2017.26openalex-snapshot
On the Relationships Between Stability and Bug-Proneness of Code Clones: An Empirical Study
inferredcites →https://doi.org/10.1109/sp.2017.62openalex-snapshot
VUDDY: A Scalable Approach for Vulnerable Code Clone Discovery
inferredcites →https://doi.org/10.1109/tse.2002.1019480openalex-snapshot
CCFinder: a multilinguistic token-based code clone detection system for large scale source code
inferredcites →https://doi.org/10.1109/tse.2018.2880977openalex-snapshot
A Systematic Literature Review on Bad Smells–5 W's: Which, When, What, Who, Where
inferredcites →https://doi.org/10.1109/wcre.2001.957835openalex-snapshot
Identifying similar code with program dependence graphs
inferredcites →https://doi.org/10.1145/1081706.1081737openalex-snapshot
An empirical study of code clone genealogies
inferredcites →https://doi.org/10.1145/1287624.1287634openalex-snapshot
Context-based detection of clone-related bugs
inferredcites →https://doi.org/10.1145/1368088openalex-snapshot
Proceedings of the 30th international conference on Software engineering
inferredcites →https://doi.org/10.1145/1370750.1370773openalex-snapshot
What do large commits tell us?
inferredcites →https://doi.org/10.1145/2245276.2231969openalex-snapshot
Comparative stability of cloned and non-cloned code
inferredcites →https://doi.org/10.1145/2560537openalex-snapshot
Comprehensive formal verification of an OS microkernel
inferredcites →https://doi.org/10.1145/2786805.2803183openalex-snapshot
Commit guru: analytics and risk prediction of software commits
inferredcites →https://doi.org/10.1145/2901739.2903496openalex-snapshot
The relationship between commit message detail and defect proneness in Java projects on GitHub
inferredcites →https://doi.org/10.1145/3213846.3213866openalex-snapshot
An empirical study on TensorFlow program bugs
inferredcites →https://doi.org/10.1145/3338906.3338955openalex-snapshot
A comprehensive study on deep learning bug characteristics
inferredcites →https://doi.org/10.1145/337180openalex-snapshot
Proceedings of the 22nd international conference on Software engineering - ICSE '00
inferredcites →https://doi.org/10.1145/3379597.3387479openalex-snapshot
The Scent of Deep Learning Code
inferredcites →https://doi.org/10.1145/3475716.3475784openalex-snapshot
The Existence and Co-Modifications of Code Clones within or across Microservices
inferredcites →https://doi.org/10.1145/581339openalex-snapshot
Proceedings of the 24th international conference on Software engineering - ICSE '02
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1002/smr.70090openalex-snapshot
Exploring Neural Network Structure Code Reuse in the Open‐Source Community for Improving Maintenance
inferred← citeshttps://doi.org/10.1007/s10515-026-00685-yopenalex-snapshot
AMCD: an adjacency matrix-based code clone detection method
inferred← citeshttps://doi.org/10.1016/j.jss.2026.112869openalex-snapshot
Unveiling code clones in the Eclipse IIoT software ecosystem
inferred← citeshttps://doi.org/10.1109/icse55347.2025.00072openalex-snapshot
PairSmell: A Novel Perspective Inspecting Software Modular Structure
inferred← citeshttps://doi.org/10.1109/icse55347.2025.00123openalex-snapshot
Code Cloning in Solidity Smart Contracts: Prevalence, Evolution, and Impact on Development
inferred← citeshttps://doi.org/10.1145/3652620.3688201openalex-snapshot
Contract-based Validation of Conceptual Design Bugs for Engineering Complex Machine Learning Software
inferred← citeshttps://doi.org/10.1145/3705303openalex-snapshot
Understanding the OSS Communities of Deep Learning Frameworks: A Comparative Case Study of P y T orch and T ensor F low
inferred← citeshttps://doi.org/10.1145/3721125openalex-snapshot
Unraveling Code Clone Dynamics in Deep Learning Frameworks
inferred← citeshttps://doi.org/10.1145/3747347openalex-snapshot
Understanding Open Source Contributor Profiles in Popular Machine Learning Libraries
inferred← citeshttps://doi.org/10.3390/app15137165openalex-snapshot
A Scoping Review and Assessment Framework for Technical Debt in the Development and Operation of AI/ML Competition Platforms
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