Automatic Software Repair: a Bibliography

Abstract

This article presents a survey on automatic software repair. Automatic software repair consists of automatically finding a solution to software bugs without human intervention. This article considers all kinds of repairs. First, it discusses behavioral repair where test suites, contracts, models, and crashing inputs are taken as oracle. Second, it discusses state repair, also known as runtime repair or runtime recovery, with techniques such as checkpoint and restart, reconfiguration, and invariant restoration. The uniqueness of this article is that it spans the research communities that contribute to this body of knowledge: software engineering, dependability, operating systems, programming languages, and security. It provides a novel and structured overview of the diversity of bug oracles and repair operators used in the literature.

References in corpus (4)

• Microreboot -- A Technique for Cheap Recovery
• Automatic Repair of Real Bugs in Java: A Large-Scale Experiment on the Defects4J Dataset
• Automated Fixing of Programs with Contracts
• Automatic Repair of Infinite Loops

Cited by in corpus (36)

• SequenceR: Sequence-to-Sequence Learning for End-to-End Program Repair
• TBar: Revisiting Template-based Automated Program Repair
• FixMiner: Mining Relevant Fix Patterns for Automated Program Repair
• Neural Program Repair with Execution-based Backpropagation
• Deep Learning for Source Code Modeling and Generation: Models, Applications and Challenges
• On the Efficiency of Test Suite based Program Repair: A Systematic Assessment of 16 Automated Repair Systems for Java Programs
• Bears: An Extensible Java Bug Benchmark for Automatic Program Repair Studies
• SelfAPR: Self-supervised Program Repair with Test Execution Diagnostics
• Automated Classification of Overfitting Patches with Statically Extracted Code Features
• How to Design a Program Repair Bot? Insights from the Repairnator Project
• A Comprehensive Study of Automatic Program Repair on the QuixBugs Benchmark
• QED at Large: A Survey of Engineering of Formally Verified Software
• Explainable Software Bot Contributions: Case Study of Automated Bug Fixes
• ITER: Iterative Neural Repair for Multi-Location Patches
• A Survey of Automated Programming Hint Generation -- The HINTS Framework
• Bidirectional Evaluation with Direct Manipulation
• Repairnator patches programs automatically
• Neural Program Repair: Systems, Challenges and Solutions
• IntRepair: Informed Repairing of Integer Overflows
• RepairLLaMA: Efficient Representations and Fine-Tuned Adapters for Program Repair
• Proof Repair across Type Equivalences
• RESTORE: Retrospective Fault Localization Enhancing Automated Program Repair
• Styler: learning formatting conventions to repair Checkstyle violations
• Automated Repair of Resource Leaks in Android Applications
• A Comprehensive Study of Code-removal Patches in Automated Program Repair
• Learning the Relation between Code Features and Code Transforms with Structured Prediction
• Fully Automated HTML and Javascript Rewriting for Constructing a Self-healing Web Proxy
• Practical Program Repair via Preference-based Ensemble Strategy
• Test-based Patch Clustering for Automatically-Generated Patches Assessment
• Enabling Automatic Repair of Source Code Vulnerabilities Using Data-Driven Methods
• A Data-to-Product Multimodal Conceptual Framework to Achieve Automated Software Evolution for Context-rich Intelligent Applications
• Estimating the Potential of Program Repair Search Spaces with Commit Analysis
• TripleAgent: Monitoring, Perturbation and Failure-obliviousness for Automated Resilience Improvement in Java Applications
• Assessing the Latent Automated Program Repair Capabilities of Large Language Models using Round-Trip Translation
• ASAP-Repair: API-Specific Automated Program Repair Based on API Usage Graphs
• An Empirical Investigation of Command-Line Customization