相关论文: Automated Repair of OpenID Connect Programs (Exten…

Deep learning models for visual recognition often exhibit systematic errors due to underrepresented semantic subpopulations. Although existing debugging frameworks can pinpoint these failures by identifying key failure attributes, repairing…

Automated Program Repair (APR) can reduce the time developers spend debugging, allowing them to focus on other aspects of software development. Automatically generated bug patches are typically validated through software testing. However,…

Recent studies have explored the performance of Large Language Models (LLMs) on various Software Engineering (SE) tasks, such as code generation and bug fixing. However, these approaches typically rely on the context data from the current…

Open-source code is pervasive. In this setting, embedded vulnerabilities are spreading to downstream software at an alarming rate. While such vulnerabilities are generally identified and addressed rapidly, inconsistent maintenance policies…

The increasing reliance of software projects on third-party libraries has raised concerns about the security of these libraries due to hidden vulnerabilities. Managing these vulnerabilities is challenging due to the time gap between fixes…

Benchmarks play an important role in evaluating the efficiency and effectiveness of solutions to automate several phases of the software development lifecycle. Moreover, if well designed, they also serve us well as an important artifact to…

Deep learning (DL) frameworks serve as the backbone for a wide range of artificial intelligence applications. However, bugs within DL frameworks can cascade into critical issues in higher-level applications, jeopardizing reliability and…

Web-based single sign-on (SSO) services such as Google Sign-In and Log In with Paypal are based on the OpenID Connect protocol. This protocol enables so-called relying parties to delegate user authentication to so-called identity providers.…

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…

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 buggy programs and…

Automated feedback generation for introductory programming assignments is useful for programming education. Most works try to generate feedback to correct a student program by comparing its behavior with an instructor's reference program on…

Smart contract vulnerabilities can cause substantial financial losses due to the immutability of code after deployment. While existing tools detect vulnerabilities, they cannot effectively repair them. In this paper, we propose SCPatcher, a…

Large language models (LLMs), such as OpenAI's Codex, have demonstrated their potential to generate code from natural language descriptions across a wide range of programming tasks. Several benchmarks have recently emerged to evaluate the…

Background: Over the years, Automated Program Repair (APR) has attracted much attention from both academia and industry since it can reduce the costs in fixing bugs. However, how to assess the patch correctness remains to be an open…

One of the most important tasks related to managing bug reports is localizing the fault so that a fix can be applied. As such, prior work has aimed to automate this task of bug localization by formulating it as an information retrieval…

Large language models (LLMs) have demonstrated impressive capabilities in generating software code for high-level programming languages such as Python and C++. However, their application to hardware description languages, such as Verilog,…

Retrieving the correct set of files from a large codebase is a crucial step in Automated Program Repair (APR). High recall is necessary to ensure that the relevant files are included, but simply increasing the number of retrieved files…

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…

Smart contracts are pieces of code that reside inside the blockchains and can be triggered to execute any transaction when specifically predefined conditions are satisfied. Being commonly used for commercial transactions in blockchain makes…

Recently, neural networks have spread into numerous fields including many safety-critical systems. Neural networks are built (and trained) by programming in frameworks such as TensorFlow and PyTorch. Developers apply a rich set of…