Papers Program Repair
“Program Repair” 태그가 달린 논문 192편 · 필터 해제
Human-In-The-Loop Automatic Program Repair
We introduce Learn2fix, the first human-in-the-loop, semi-automatic repair technique when no bug oracle--except for the user who is reporting the bug--is available. Our approach negotiates with the user the condition und…
Program RepairLearning to Fix Build Errors with Graph2Diff Neural Networks
Professional software developers spend a significant amount of time fixing builds, but this has received little attention as a problem in automatic program repair. We present a new deep learning architecture, called Grap…
DiagnosticGraph Neural NetworkProgram RepairSampleFix: Learning to Generate Functionally Diverse Fixes
Automatic program repair holds the potential of dramatically improving the productivity of programmers during the software development process and correctness of software in general. Recent advances in machine learning, …
DiversityProgram RepairENCORE: Ensemble Learning using Convolution Neural Machine Translation for Automatic Program Repair
Automated generate-and-validate (G&V) program repair techniques typically rely on hard-coded rules, only fix bugs following specific patterns, and are hard to adapt to different programming languages. We propose ENCORE, …
Ensemble LearningMachine TranslationNMTProgram Repair+1Neural Program Repair by Jointly Learning to Localize and Repair
Due to its potential to improve programmer productivity and software quality, automated program repair has been an active topic of research. Newer techniques harness neural networks to learn directly from examples of bug…
Program RepairVariable misuseSequenceR: Sequence-to-Sequence Learning for End-to-End Program Repair
This paper presents a novel end-to-end approach to program repair based on sequence-to-sequence learning. We devise, implement, and evaluate a system, called SequenceR, for fixing bugs based on sequence-to-sequence learn…
Program RepairTowards Mixed Optimization for Reinforcement Learning with Program Synthesis
Deep reinforcement learning has led to several recent breakthroughs, though the learned policies are often based on black-box neural networks. This makes them difficult to interpret and to impose desired specification co…
Deep Reinforcement LearningProgram RepairProgram Synthesisreinforcement-learning+2Deep Reinforcement Learning for Programming Language Correction
Novice programmers often struggle with the formal syntax of programming languages. To assist them, we design a novel programming language correction framework amenable to reinforcement learning. The framework allows an a…
Deep Reinforcement LearningMachine TranslationProgram Repairreinforcement-learning+3Dynamic Neural Program Embeddings for Program Repair
Neural program embeddings have shown much promise recently for a variety of program analysis tasks, including program synthesis, program repair, code completion, and fault localization. However, most existing program emb…
Code CompletionFault localizationProgram RepairProgram SynthesisDynamic Neural Program Embedding for Program Repair
Neural program embeddings have shown much promise recently for a variety of program analysis tasks, including program synthesis, program repair, fault localization, etc. However, most existing program embeddings are base…
Fault localizationProgram RepairProgram SynthesisSmartPaste: Learning to Adapt Source Code
Deep Neural Networks have been shown to succeed at a range of natural language tasks such as machine translation and text summarization. While tasks on source code (ie, formal languages) have been considered recently, mo…
Machine TranslationProgram RepairText SummarizationTranslationDeepFix: Fixing Common C Language Errors by Deep Learning
The problem of automatically fixing programming errors is a very active research topic in software engineering. This is a challenging problem as fixing even a single error may require analysis of the entire program. In p…
Deep LearningProgram Repair