Variable misuse

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Most implemented papers archive 2025-07-28

11 shown of 11 papers with code (15 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Graph Conditioned Sparse-Attention for Improved Source Code Understanding
  1 Dec 2021 2 repositories listed
  The fusion between a graph representation like Abstract Syntax Tree (AST) and a source code sequence makes the use of current approaches computationally intractable for large input sequence lengths.
• Memorization and Generalization in Neural Code Intelligence Models
  16 Jun 2021 2 repositories listed
  The goal of this paper is to evaluate and compare the extent of memorization and generalization in neural code intelligence models.
• Understanding Neural Code Intelligence Through Program Simplification
  7 Jun 2021 2 repositories listed
  Our approach, SIVAND, uses simplification techniques that reduce the size of input programs of a CI model while preserving the predictions of the model.
• Learning and Evaluating Contextual Embedding of Source Code
  21 Dec 2019 2 repositories listed
  We fine-tune CuBERT on our benchmark tasks, and compare the resulting models to different variants of Word2Vec token embeddings, BiLSTM and Transformer models, as well as published state-of-the-art models, showing that…
• Neural Program Repair by Jointly Learning to Localize and Repair
  3 Apr 2019 2 repositories listed Syntology ran 0 of 8 samples · 8 unverified
  We show that it is beneficial to train a model that jointly and directly localizes and repairs variable-misuse bugs.
• The Power of Types: Exploring the Impact of Type Checking on Neural Bug Detection in Dynamically Typed Languages
  22 Nov 2024 1 repository listed
  Problem: However, prior studies overlook this aspect during the training and testing of neural bug detectors for dynamically typed languages.
• A Critical Study of What Code-LLMs (Do Not) Learn
  17 Jun 2024 1 repository listed
  Some studies argue that code-LLMs perform well on coding tasks because they use self-attention and hidden representations to encode relations among input tokens.
• Probing Pretrained Models of Source Code
  16 Feb 2022 1 repository listed
  Deep learning models are widely used for solving challenging code processing tasks, such as code generation or code summarization.
• CodeTrek: Flexible Modeling of Code using an Extensible Relational Representation
  29 Sep 2021 1 repository listed
  Designing a suitable representation for code-reasoning tasks is challenging in aspects such as the kinds of program information to model, how to combine them, and how much context to consider.
• Learning Graph Structure With A Finite-State Automaton Layer
  9 Jul 2020 1 repository listed
  In practice, edges are used both to represent intrinsic structure (e.
• Global Relational Models of Source Code
  1 May 2020 1 repository listed
  By studying a popular, non-trivial program repair task, variable-misuse identification, we explore the relative merits of traditional and hybrid model families for code representation.

Syntology lines on 1 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.