skip to main content
10.1145/3387940.3392181acmconferencesArticle/Chapter ViewAbstractPublication PagesicseConference Proceedingsconference-collections
short-paper
Open access

Learning to Fix Build Errors with Graph2Diff Neural Networks

Published: 25 September 2020 Publication History
  • Get Citation Alerts
  • Abstract

    No abstract available.

    References

    [1]
    Miltiadis Allamanis, Marc Brockschmidt, and Mahmoud Khademi. 2018. Learning to represent programs with graphs. In ICLR.
    [2]
    Miltiadis Allamanis, Hao Peng, and Charles Sutton. 2016. A convolutional attention network for extreme summarization of source code. In International Conference on Machine Learning. 2091--2100.
    [3]
    Miltiadis Allamanis and Charles Sutton. 2013. Mining source code repositories at massive scale using language modeling. In Proceedings of the 10th Working Conference on Mining Software Repositories. IEEE Press, 207--216.
    [4]
    Joshua Charles Campbell, Abram Hindle, and José Nelson Amaral. 2014. Syntax errors just aren't natural: improving error reporting with language models. In Working Conference on Mining Software Repositories (MSR). 252--261.
    [5]
    Rahul Gupta, Soham Pal, Aditya Kanade, and Shirish Shevade. 2017. Deepfix: Fixing common C language errors by deep learning. In Thirty-First AAAI Conference on Artificial Intelligence.
    [6]
    Vincent J. Hellendoorn and Premkumar Devanbu. 2017. Are Deep Neural Networks the Best Choice for Modeling Source Code?. In Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering (ESEC/FSE 2017). ACM, New York, NY, USA, 763--773. https://doi.org/10.1145/3106237.3106290
    [7]
    Rafael-Michael Karampatsis and Charles Sutton. 2019. Maybe Deep Neural Networks are the Best Choice for Modeling Source Code. CoRR abs/1903.05734 (2019). arXiv:1903.05734 http://arxiv.org/abs/1903.05734
    [8]
    Yujia Li, Daniel Tarlow, Marc Brockschmidt, and Richard Zemel. 2016. Gated graph sequence neural networks. In ICLR.
    [9]
    Kui Liu, Anil Koyuncu, Tegawendé F Bissyandé, Dongsun Kim, Jacques Klein, and Yves Le Traon. 2019. You cannot fix what you cannot find! an investigation of fault localization bias in benchmarking automated program repair systems. In 2019 12th IEEE Conf. on Software Testing, Validation and Verification (ICST). IEEE, 102--113.
    [10]
    Ali Mesbah, Andrew Rice, Emily Johnston, Nick Glorioso, and Edward Aftandilian. 2019. DeepDelta: Learning To Repair Compilation Errors. In Proc. of the 2019 27th European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE 2019). ACM, New York, NY, USA.
    [11]
    Franco Scarselli, Marco Gori, Ah Chung Tsoi, Markus Hagenbuchner, and Gabriele Monfardini. 2009. The graph neural network model. IEEE Transactions on Neural Networks (2009).
    [12]
    Hyunmin Seo, Caitlin Sadowski, Sebastian Elbaum, Edward Aftandilian, and Robert Bowdidge. 2014. Programmers' build errors: A case study (at Google). In International Conference on Software Engineering. ACM, 724--734.
    [13]
    Oriol Vinyals, Meire Fortunato, and Navdeep Jaitly. 2015. Pointer Networks. In Advances in Neural Information Processing Systems 28. 2692--2700.
    [14]
    Rui Zhao, David Bieber, Kevin Swersky, and Daniel Tarlow. 2019. Neural Networks for Modeling Source Code Edits. arXiv preprint arXiv:1904.02818 (2019).

    Cited By

    View all
    • (2024)On the Heterophily of Program Graphs: A Case Study of Graph-based Type InferenceProceedings of the 15th Asia-Pacific Symposium on Internetware10.1145/3671016.3671389(1-10)Online publication date: 24-Jul-2024
    • (2024)A Deep Dive into Large Language Models for Automated Bug Localization and RepairProceedings of the ACM on Software Engineering10.1145/36607731:FSE(1471-1493)Online publication date: 12-Jul-2024
    • (2024)Automated Code Editing with Search-Generate-ModifyProceedings of the 2024 IEEE/ACM 46th International Conference on Software Engineering: Companion Proceedings10.1145/3639478.3643124(398-399)Online publication date: 14-Apr-2024
    • Show More Cited By

    Index Terms

    1. Learning to Fix Build Errors with Graph2Diff Neural Networks
          Index terms have been assigned to the content through auto-classification.

          Recommendations

          Comments

          Please enable JavaScript to view thecomments powered by Disqus.

          Information & Contributors

          Information

          Published In

          cover image ACM Conferences
          ICSEW'20: Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops
          June 2020
          831 pages
          ISBN:9781450379632
          DOI:10.1145/3387940
          This work is licensed under a Creative Commons Attribution International 4.0 License.

          Sponsors

          Publisher

          Association for Computing Machinery

          New York, NY, United States

          Publication History

          Published: 25 September 2020

          Permissions

          Request permissions for this article.

          Check for updates

          Qualifiers

          • Short-paper
          • Research
          • Refereed limited

          Conference

          ICSE '20
          Sponsor:
          ICSE '20: 42nd International Conference on Software Engineering
          June 27 - July 19, 2020
          Seoul, Republic of Korea

          Upcoming Conference

          ICSE 2025

          Contributors

          Other Metrics

          Bibliometrics & Citations

          Bibliometrics

          Article Metrics

          • Downloads (Last 12 months)344
          • Downloads (Last 6 weeks)26
          Reflects downloads up to 14 Aug 2024

          Other Metrics

          Citations

          Cited By

          View all
          • (2024)On the Heterophily of Program Graphs: A Case Study of Graph-based Type InferenceProceedings of the 15th Asia-Pacific Symposium on Internetware10.1145/3671016.3671389(1-10)Online publication date: 24-Jul-2024
          • (2024)A Deep Dive into Large Language Models for Automated Bug Localization and RepairProceedings of the ACM on Software Engineering10.1145/36607731:FSE(1471-1493)Online publication date: 12-Jul-2024
          • (2024)Automated Code Editing with Search-Generate-ModifyProceedings of the 2024 IEEE/ACM 46th International Conference on Software Engineering: Companion Proceedings10.1145/3639478.3643124(398-399)Online publication date: 14-Apr-2024
          • (2024)Resolving Code Review Comments with Machine LearningProceedings of the 46th International Conference on Software Engineering: Software Engineering in Practice10.1145/3639477.3639746(204-215)Online publication date: 14-Apr-2024
          • (2024)Automated Code Editing with Search-Generate-ModifyIEEE Transactions on Software Engineering10.1109/TSE.2024.3376387(1-12)Online publication date: 2024
          • (2024)Smart Contract Vulnerability Detection Using Deep Learning Algorithms on EVM bytecode2024 13th Mediterranean Conference on Embedded Computing (MECO)10.1109/MECO62516.2024.10577852(1-7)Online publication date: 11-Jun-2024
          • (2024)Improving Code Representation Learning via Multi-view Contrastive Graph Pooling for Abstract Syntax TreeCollaborative Computing: Networking, Applications and Worksharing10.1007/978-3-031-54528-3_14(242-261)Online publication date: 23-Feb-2024
          • (2023)Neural Transfer Learning for Repairing Security Vulnerabilities in C CodeIEEE Transactions on Software Engineering10.1109/TSE.2022.314726549:1(147-165)Online publication date: 1-Jan-2023
          • (2023)On the Reproducibility of Software Defect Datasets2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE)10.1109/ICSE48619.2023.00195(2324-2335)Online publication date: May-2023
          • (2023)KNOD: Domain Knowledge Distilled Tree Decoder for Automated Program RepairProceedings of the 45th International Conference on Software Engineering10.1109/ICSE48619.2023.00111(1251-1263)Online publication date: 14-May-2023
          • Show More Cited By

          View Options

          View options

          PDF

          View or Download as a PDF file.

          PDF

          eReader

          View online with eReader.

          eReader

          Get Access

          Login options

          Media

          Figures

          Other

          Tables

          Share

          Share

          Share this Publication link

          Share on social media