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Automated program repair (APR) has achieved promising results, especially using neural networks. Yet, the overwhelming majority of patches produced by APR tools are confined to one single location. When looking at the patches produced with…
Automatic Program Repair (APR) is a brilliant idea: when detecting a bug, also provide suggestions for correcting the program. Progress towards that goal is hindered by the absence of a common frame of reference for the multiplicity of APR…
Automated program repair (APR) techniques have achieved conspicuous progress, and are now capable of producing genuinely correct fixes in scenarios that were well beyond their capabilities only a few years ago. Nevertheless, even when an…
Automated program repair (APR) aims to fix software bugs automatically and plays a crucial role in software development and maintenance. With the recent advances in deep learning (DL), an increasing number of APR techniques have been…
Large Language Model (LLM) - based Automated Program Repair (APR) systems are increasingly integrated into modern software development workflows, offering automated patches in response to natural language bug reports. However, this reliance…
Automated Program Repair (APR) techniques have shown more and more promising results in fixing real-world bugs. Despite the effectiveness, APR techniques still face an overfitting problem: a generated patch can be incorrect although it…
Automated program repair (APR) using deep learning techniques has become an important area of research in recent years, aiming to automatically generate bug-fixing patches that can improve software reliability and maintainability. However,…
(Note: This work is a preprint.) Static analysis (SA) tools produce many diagnostic alerts indicating that source code in C or C++ may be defective and potentially vulnerable to security exploits. Many of these alerts are false positives.…
Properly benchmarking Automated Program Repair (APR) systems should contribute to the development and adoption of the research outputs by practitioners. To that end, the research community must ensure that it reaches significant milestones…
The characterization of bug datasets is essential to support the evaluation of automatic program repair tools. In a previous work, we manually studied almost 400 human-written patches (bug fixes) from the Defects4J dataset and annotated…
Automated Program Repair (APR) has garnered significant attention due to its potential to streamline the bug repair process for human developers. Recently, LLM-based APR methods have shown promise in repairing real-world bugs. However,…
Automatic program repair (APR) aims to reduce the cost of manually fixing software defects. However, APR suffers from generating a multitude of overfitting patches, those patches that fail to correctly repair the defect beyond making the…
Automated Program Repair (APR) techniques typically rely on a given test-suite to guide the repair process. Apart from the need to provide test oracles, this makes the produced patches prone to test data over-fitting. In this work, instead…
In the context of test case based automated program repair (APR), the research community call the patches that pass all the test cases but fail to actually fix the bug test case overfitted patches. Currently, overfitted patches has to be…
Automated Program Repair (APR) seeks to automatically correct software bugs without requiring human intervention. However, existing tools tend to generate patches that satisfy test cases without fixing the underlying bug, those are known as…
Bug Reproduction Tests (BRTs) have been used in many Automated Program Repair (APR) systems, primarily for validating promising fixes and aiding fix generation. In practice, when developers submit a patch, they often implement the BRT…
Automated Program Repair (APR) is a vital area in software engineering aimed at generating automatic patches for vulnerable programs. While numerous techniques have been proposed for repairing classical programs, the realm of quantum…
Various automated program repair (APR) techniques have been proposed to fix bugs automatically in the last decade. Although recent researches have made significant progress on the effectiveness and efficiency, it is still unclear how APR…
Automated Program Repair (APR) aims to automatically generate correct patches for buggy programs. Recent approaches leveraging large language models (LLMs) have shown promise but face limitations. Most rely solely on static analysis,…
Automated Vulnerability Repair (AVR) systems, especially those leveraging large language models (LLMs), have demonstrated promising results in patching vulnerabilities -- that is, if we trust their patch validation methodology. Ground-truth…