Papers Program Repair
“Program Repair” 태그가 달린 논문 192편 · 필터 해제
A Syntax-Guided Edit Decoder for Neural Program Repair
Automated Program Repair (APR) helps improve the efficiency of software development and maintenance. Recent APR techniques use deep learning, particularly the encoder-decoder architecture, to generate patches. Though exi…
Code CompletionCode GenerationDecoderProgram RepairAssessing the Effectiveness of Syntactic Structure to Learn Code Edit Representations
In recent times, it has been shown that one can use code as data to aid various applications such as automatic commit message generation, automatic generation of pull request descriptions and automatic program repair. Ta…
Machine TranslationProgram RepairBreak-It-Fix-It: Unsupervised Learning for Program Repair
We consider repair tasks: given a critic (e.g., compiler) that assesses the quality of an input, the goal is to train a fixer that converts a bad example (e.g., code with syntax errors) into a good one (e.g., code with n…
C++ codeCode RepairData AugmentationDomain Adaptation+3DeepDebug: Fixing Python Bugs Using Stack Traces, Backtranslation, and Code Skeletons
The joint task of bug localization and program repair is an integral part of the software development process. In this work we present DeepDebug, an approach to automated debugging using large, pretrained transformers. W…
Program RepairProgram Repair with Repeated Learning
A key challenge in generate-and-validate automated program repair is directing the search for fixes so that it can efficiently find those that are more likely to be correct. To this end, several techniques use machine le…
Program RepairGenerating Bug-Fixes Using Pretrained Transformers
Detecting and fixing bugs are two of the most important yet frustrating parts of the software development cycle. Existing bug detection tools are based mainly on static analyzers, which rely on mathematical logic and sym…
DenoisingProgram RepairExploring Plausible Patches Using Source Code Embeddings in JavaScript
Despite the immense popularity of the Automated Program Repair (APR) field, the question of patch validation is still open. Most of the present-day approaches follow the so-called Generate-and-Validate approach, where fi…
Program RepairUnified Pre-training for Program Understanding and Generation
Code summarization and generation empower conversion between programming language (PL) and natural language (NL), while code translation avails the migration of legacy code from one PL to another. This paper introduces P…
Clone DetectionCode GenerationCode SummarizationCode Translation+5CURE: Code-Aware Neural Machine Translation for Automatic Program Repair
Automatic program repair (APR) is crucial to improve software reliability. Recently, neural machine translation (NMT) techniques have been used to fix software bugs automatically. While promising, these approaches have t…
Machine TranslationNMTProgram RepairTranslationFairness-guided SMT-based Rectification of Decision Trees and Random Forests
Data-driven decision making is gaining prominence with the popularity of various machine learning models. Unfortunately, real-life data used in machine learning training may capture human biases, and as a result the lear…
BIG-bench Machine LearningDecision MakingFairnessProgram RepairObstacles in Fully Automatic Program Repair: A survey
The current article is an interdisciplinary attempt to decipher automatic program repair processes. The review is done by the manner typical to human science known as diffraction. We attempt to spot a gap in the literatu…
Program RepairSurveyLearning to Execute Programs with Instruction Pointer Attention Graph Neural Networks
Graph neural networks (GNNs) have emerged as a powerful tool for learning software engineering tasks including code completion, bug finding, and program repair. They benefit from leveraging program structure like control…
Code CompletionLearning to ExecuteProgram RepairProgram Synthesis+1Patching as Translation: the Data and the Metaphor
Machine Learning models from other fields, like Computational Linguistics, have been transplanted to Software Engineering tasks, often quite successfully. Yet a transplanted model's initial success at a given task does n…
General KnowledgeProgram RepairTranslationRobot Action Selection Learning via Layered Dimension Informed Program Synthesis
Action selection policies (ASPs), used to compose low-level robot skills into complex high-level tasks are commonly represented as neural networks (NNs) in the state of the art. Such a paradigm, while very effective, suf…
Autonomous DrivingProgram RepairProgram SynthesisCoCoNuT: Combining Context-Aware Neural Translation Models using Ensemble for Program Repair
Automated generate-and-validate (GV) program repair techniques (APR) typically rely on hard-coded rules, thus only fixing bugs following specific fix patterns. These rules require a significant amount of manual effort to…
Ensemble LearningMachine TranslationNMTProgram Repair+1Graph-based, Self-Supervised Program Repair from Diagnostic Feedback
We consider the problem of learning to repair programs from diagnostic feedback (e.g., compiler error messages). Program repair is challenging for two reasons: First, it requires reasoning and tracking symbols across sou…
Code GenerationDiagnosticGraph LearningGraph Neural Network+3Global Relational Models of Source Code
Models of code can learn distributed representations of a program's syntax and semantics to predict many non-trivial properties of a program. Recent state-of-the-art models leverage highly structured representations of p…
Inductive BiasProgram RepairVariable misuseSCELMo: Source Code Embeddings from Language Models
Continuous embeddings of tokens in computer programs have been used to support a variety of software development tools, including readability, code search, and program repair. Contextual embeddings are common in natural …
Code SearchProgram RepairArachne: Search Based Repair of Deep Neural Networks
The rapid and widespread adoption of Deep Neural Networks (DNNs) has called for ways to test their behaviour, and many testing approaches have successfully revealed misbehaviour of DNNs. However, it is relatively unclear…
FairnessGender ClassificationProgram RepairLearning and Evaluating Contextual Embedding of Source Code
Recent research has achieved impressive results on understanding and improving source code by building up on machine-learning techniques developed for natural languages. A significant advancement in natural-language unde…
Contextual Embedding for Source CodeException typeFunction-docstring mismatchNatural Language Understanding+4