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Machine learning (ML) now pervades the field of Automated Program Repair (APR).
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Towards Making Systems Forget with Machine Unlearning. In 2015 IEEE Symposium on Security and Privacy . IEEE, San Jose, CA, 463–480
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The ManyBugs and IntroClass Benchmarks for Automated Repair of C Programs
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Prophet: Automatic Patch Generation via Learning from Successful Patches
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Angelix: Scalable Multiline Program Patch Synthesis via Symbolic Analysis. In International Conference on Software Engineering . ACM, Austin, TX, USA, 691–701
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Quixbugs: A Multi-Lingual Program Repair Benchmark Set Based on the Quixey Challenge. In Proceedings Companion of the 2017 ACM SIGPLAN International Conference on Systems, Programming, Languages, and Applications: Software for Humanity . ACM, 55–56
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DéjàVu: a map of code duplicates on GitHub
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Codeflaws: A Programming Competition Benchmark for Evaluating Automated Program Repair Tools. In Proceedings of the 39th International Conference on Software Engineering Companion . IEEE Press, 180–182
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Attention Is All You Need
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Neuro-Symbolic Program Corrector for Introductory Programming Assignments. In Proceedings of the 40th International Conference on Software Engineering . ACM, Gothenburg Sweden, 60–70
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Efficient Repair of Polluted Machine Learning Systems via Causal Unlearning. In Proceedings of the 2018 on Asia Conference on Computer and Communications Security . ACM, Incheon Republic of Korea, 735–747
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Black-box generation of adversarial text sequences to evade deep learning classifiers. In 2018 IEEE Security and Privacy Workshops (SPW) . IEEE, 50–56
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SketchFix: a tool for automated program repair approach using lazy candidate generation. In Proceedings of the 2018 ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering, ESEC/SIGSOFT FSE 2018, Lake Buena Vista, FL, USA, November 04-09, 2018 , Gary T. Leavens, Alessandro Garcia, and Corina S. Pasareanu (Eds.). ACM, 888–891
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Do automated program repair techniques repair hard and important bugs?
Manish Motwani, Sandhya Sankaranarayanan, René Just, and Yuriy Brun. 2018 · 2018
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A comparison of code similarity analysers
Chaiyong Ragkhitwetsagul, Jens Krinke, and David Clark. 2018 · 2018
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Bugs.Jar: A Large-Scale, Diverse Dataset of Real-World Java Bugs. In Proceedings of the 15th International Conference on Mining Software Repositories - MSR ’18 . ACM Press, Gothenburg, Sweden, 10–13
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Context-Aware Patch Generation for Better Automated Program Repair. In Proceedings of the 40th International Conference on Software Engineering . ACM, Gothenburg Sweden, 1–11
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The Adverse Effects of Code Duplication in Machine Learning Models of Code. In Proceedings of the 2019 ACM SIGPLAN International Symposium on New Ideas, New Paradigms, and Reflections on Programming and Software (Athens, Greece) (Onward! 2019) . Association for Computing Machinery, New York, NY, USA, 143–153
Miltiadis Allamanis. 2019 · 2019
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Nuanced Metrics for Measuring Unintended Bias with Real Data for Text Classification. In Companion Proceedings of The 2019 World Wide Web Conference . ACM, San Francisco USA, 491–500
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The Secret Sharer: Evaluating and Testing Unintended Memorization in Neural Networks. In USENIX Security , Vol. 28. USENIX
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Understanding Automatically-Generated Patches Through Symbolic Invariant Differences. In Automated Software Engineering . IEEE, 411–414
Padraic Cashin, Carianne Martinez, Westley Weimer, and Stephanie Forrest. 2019 · 2019
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BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
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Automatic Software Repair: A Survey
Luca Gazzola, Daniela Micucci, and Leonardo Mariani. 2019 · 2019
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Toward Practical Automatic Program Repair. In 34th IEEE/ACM International Conference on Automated Software Engineering, ASE 2019, San Diego, CA, USA, November 11-15, 2019 . IEEE, 1262–1264
Ali Ghanbari. 2019 · 2019
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PraPR: Practical Program Repair via Bytecode Mutation. In 34th IEEE/ACM International Conference on Automated Software Engineering, ASE 2019, San Diego, CA, USA, November 11-15, 2019 . IEEE, 1118–1121
Ali Ghanbari and Lingming Zhang. 2019 · 2019
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Automatic patch generation with context-based change application
Jindae Kim and Sunghun Kim. 2019 · 2019
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iFixR: Bug Report Driven Program Repair. In Proceedings of the 2019 27th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering . ACM, Tallinn Estonia, 314–325
Anil Koyuncu, Kui Liu, Tegawendé F. Bissyandé, Dongsun Kim, Martin Monperrus, et al · 2019
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Automated Program Repair
Claire Le Goues, Michael Pradel, and Abhik Roychoudhury. 2019 · 2019
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TBar: Revisiting Template-based Automated Program Repair. In International Symposium on Software Testing and Analysis . ACM, Beijing, China, 31–42
Kui Liu, Anil Koyuncu, Dongsun Kim, and Tegawendé F. Bissyandé. 2019 · 2019
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Harnessing Evolution for Multi-Hunk Program Repair. In International Conference on Software Engineering . IEEE, Montreal, QC, Canada, 13–24
Seemanta Saha, Ripon K. Saha, and Mukul R. Prasad. 2019 · 2019
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An Empirical Study on Learning Bug-Fixing Patches in the Wild via Neural Machine Translation
Michele Tufano, Cody Watson, Gabriele Bavota, Massimiliano Di Penta, Martin White, et al · 2019
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VFix: Value-Flow-Guided Precise Program Repair for Null Pointer Dereferences. In 2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE) . IEEE, Montreal, QC, Canada, 512–523
Xuezheng Xu, Yulei Sui, Hua Yan, and Jingling Xue. 2019 · 2019
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Alleviating patch overfitting with automatic test generation: a study of feasibility and effectiveness for the Nopol repair system
Zhongxing Yu, Matias Martinez, Benjamin Danglot, Thomas Durieux, and Martin Monperrus. 2019 · 2019
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Do We Train on Test Data? Purging CIFAR of Near-Duplicates
Björn Barz and Joachim Denzler. 2020 · 2020
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On the Effectiveness of Unified Debugging: An Extensive Study on 16 Program Repair Systems. In 35th IEEE/ACM International Conference on Automated Software Engineering, ASE 2020, Melbourne, Australia, September 21-25, 2020 . IEEE, 907–918
Samuel Benton, Xia Li, Yiling Lou, and Lingming Zhang. 2020 · 2020
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Language Models Are Few-Shot Learners. In Advances in Neural Information Processing Systems , Vol. 33. NIPS
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Patching as Translation: The Data and the Metaphor. In 35th IEEE/ACM International Conference on Automated Software Engineering (ASE ’20) . ACM, Virtual Event
Improving Fault Localization and Program Repair with Deep Semantic Features and Transferred Knowledge. In Proceedings of the 44th International Conference on Software Engineering . ACM, Pittsburgh Pennsylvania, 1169–1180
Xiangxin Meng, Xu Wang, Hongyu Zhang, Hailong Sun, and Xudong Liu. 2022 · 2022
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Quality of Automated Program Repair on Real-World Defects
Manish Motwani, Mauricio Soto, Yuriy Brun, Rene Just, and Claire Le Goues. 2022 · 2022
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A Controlled Experiment of Different Code Representations for Learning-Based Program Repair
Marjane Namavar, Noor Nashid, and Ali Mesbah. 2022 · 2022
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Trust Enhancement Issues in Program Repair. In Proceedings of the 44th International Conference on Software Engineering . ACM, Pittsburgh Pennsylvania, 2228–2240
Yannic Noller, Ridwan Shariffdeen, Xiang Gao, and Abhik Roychoudhury. 2022 · 2022
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Yangruibo Ding, Baishakhi Ray, Premkumar Devanbu, and Vincent J. Hellendoorn. 2020 · 2020
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A study of potential code borrowing and license violations in java projects on github. In Proceedings of the 17th International Conference on Mining Software Repositories . 54–64
Yaroslav Golubev, Maria Eliseeva, Nikita Povarov, and Timofey Bryksin. 2020 · 2020
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Deflating Dataset Bias Using Synthetic Data Augmentation. In 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) . IEEE, Seattle, WA, USA, 3344–3353
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Improved Code Summarization via a Graph Neural Network. In Proceedings of the 28th International Conference on Program Comprehension . ACM, Seoul Republic of Korea, 184–195
Alexander LeClair, Sakib Haque, Lingfei Wu, and Collin McMillan. 2020 · 2020
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BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics . Association for Computational Linguistics, Online, 7871–7880
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DLFix: Context-based Code Transformation Learning for Automated Program Repair. In International Conference on Software Engineering . ACM, Seoul, South Korea, 602–614
Yi Li, Shaohua Wang, and Tien N. Nguyen. 2020 · 2020
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On the Efficiency of Test Suite Based Program Repair: A Systematic Assessment of 16 Automated Repair Systems for Java Programs. In Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering . ACM, Seoul South Korea, 615–627
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CoCoNuT: Combining Context-Aware Neural Translation Models Using Ensemble for Program Repair. In International Symposium on Software Testing and Analysis . ACM, Virtual Event, 101–114
Thibaud Lutellier, Hung Viet Pham, Lawrence Pang, Yitong Li, Moshi Wei, et al · 2020
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PyTER: effective program repair for Python type errors. In Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, ESEC/FSE 2022, Singapore, Singapore, November 14-18, 2022 , Abhik Roychoudhury, Cristian Cadar, and Miryung Kim (Eds.). ACM, 922–934
Wonseok Oh and Hakjoo Oh. 2022 · 2022
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EleutherAI: Going Beyond" Open Science" to" Science in the Open"
Jason Phang, Herbie Bradley, Leo Gao, Louis Castricato, and Stella Biderman. 2022 · 2022
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Is This Change the Answer to That Problem?: Correlating Descriptions of Bug and Code Changes for Evaluating Patch Correctness. In Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering . ACM, Rochester MI USA, 1–13
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What Language Model Architecture and Pretraining Objective Work Best for Zero-Shot Generalization?. In International Conference on Machine Learning . 22964–22984
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Ga Wu, Masoud Hashemi, and Christopher Srinivasa. 2022 · 2022
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Less Training, More Repairing Please: Revisiting Automated Program Repair via Zero-Shot Learning. In Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering . ACM, Singapore Singapore, 959–971
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NeurIPS 2023 Machine Unlearning Challenge
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FixMiner: Mining relevant fix patterns for automated program repair
Anil Koyuncu, Kui Liu, Tegawendé F. Bissyandé, Dongsun Kim, Jacques Klein, et al · 2024
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