Related papers: Human-competitive Patches in Automatic Program Rep…
Bug fixing and code generation have been core research topics in software development for many years. The recent explosive growth in Large Language Models has completely transformed these spaces, putting in reach incredibly powerful tools…
Machine Learning approaches are good in solving problems that have less information. In most cases, the software domain problems characterize as a process of learning that depend on the various circumstances and changes accordingly. A…
Automated program repair (APR) has attracted widespread attention in recent years with substantial techniques being proposed. Meanwhile, a number of benchmarks have been established for evaluating the performances of APR techniques, among…
We compare automatically and manually parallelized NAS Benchmarks in order to identify code sections that differ. We discuss opportunities for advancing automatic parallelizers. We find ten patterns that pose challenges for current…
Despite significant advances in automatic program repair (APR)techniques over the past decade, practical deployment remains an elusive goal. One of the important challenges in this regard is the general inability of current APR techniques…
Selecting the right compiler optimisations has a severe impact on programs' performance. Still, the available optimisations keep increasing, and their effect depends on the specific program, making the task human intractable. Researchers…
Context: Learning-based automatic program repair techniques are showing promise to provide quality fix suggestions for detected bugs in the source code of the software. These tools mostly exploit historical data of buggy and fixed code…
Reproducing concurrency bugs is a complex task due to their unpredictable behavior. Researchers, regardless of gender, are contributing to automating this complex task to aid software developers. While some studies have investigated gender…
A hot fix is an unplanned improvement to a specific time-critical issue deployed to a software system in production. While hot fixing is an essential and common activity in software maintenance, it has never been surveyed as a research…
We present PTracer, a Linux kernel patch trace bot based on an improved PatchNet. PTracer continuously monitors new patches in the git repository of the mainline Linux kernel, filters out unconcerned ones, classifies the rest as bug-fixing…
Many programmers, when they encounter an error, would like to have the benefit of automatic fix suggestions---as long as they are, most of the time, adequate. Initial research in this direction has generally limited itself to specific…
Autonomous flying robots, such as multirotors, often rely on deep learning models that make predictions based on a camera image, e.g. for pose estimation. These models can predict surprising results if applied to input images outside the…
Software developers attempt to reproduce software bugs to understand their erroneous behaviours and to fix them. Unfortunately, they often fail to reproduce (or fix) them, which leads to faulty, unreliable software systems. However, to…
Programming is increasingly taught using block-based languages like Scratch. While the use of blocks prevents syntax errors, learners can still make semantic mistakes, requiring feedback and help. As teachers may be overwhelmed by help…
Automated Program Repair (APR) is a fast growing area with numerous new techniques being developed to tackle one of the most challenging software engineering problems. APR techniques have shown promising results, giving us hope that one day…
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,…
AI coding agents are increasingly integrated into modern software engineering workflows, actively collaborating with human developers to create pull requests (PRs) in open-source repositories. Although coding agents improve developer…
AI humanizers are a new class of online software tools meant to paraphrase and rewrite AI-generated text in a way that allows them to evade AI detection software. We study 19 AI humanizer and paraphrasing tools and qualitatively assess…
Recent progress in automated repair of performance bugs demands realistic, executable benchmarks. However, existing C++ performance benchmarks are largely built from competitive programming submissions, and recent real-world benchmarks…
Most automatic program repair techniques rely on test cases to specify correct program behavior. Due to test cases' frequently incomplete coverage of desired behavior, however, patches often overfit and fail to generalize to broader…