2,847 papers · page 23 of 143
GitHub’s Copilot for Pull Requests (PRs) is a promising service aiming to automate various developer tasks related to PRs, such as generating summaries of changes or providing complete walkthroughs with links to the relevant code. As this innovative technology gains traction in t…
With the increasing utilization of Machine Learning (ML) software in critical domains such as employee hiring, college admission, and credit evaluation, ensuring fairness in the decision-making processes of underlying models has emerged as a paramount ethical concern. Nonetheless…
Log analysis is one of the main techniques that engineers use for troubleshooting large-scale software systems. Over the years, many supervised, semi-supervised, and unsupervised log analysis methods have been proposed to detect system anomalies by analyzing system logs. Among th…
This paper presents our approach proposed to detect and create indivisible multi-hunk bugs, an evaluation of existing repair techniques based on these bugs, and a study of the patches of these bugs constructed by the developers and existing tools. Multi-hunk bug repair aims to de…
Program slicing, the process of extracting program statements that influence values at a designated location (known as the slicing criterion), is helpful in both manual and automated debugging. However, such slicing techniques prove ineffective in scenarios where executing specif…
Impact analysis (IA) is a critical software maintenance task that identifies the effects of a given set of code changes on a larger software project with the intention of avoiding potential adverse effects. IA is a cognitively challenging task that involves reasoning about the ab…
Android has empowered third-party apps to access data and services on mobile devices since its genesis.This involves a wide spectrum of user privacy-sensitive data, such as the device ID and location. In recent years, Android has taken proactive measures to adapt its access contr…
Code translation tools, namely transpilers, are developed for automatic source-to-source translation. Latest learning-based transpilers have shown impressive enhancement against rule-based counterparts in both translation accuracy and readability, owing to their task-specific pre…
Increasing studies have shown bugs in multi-language software as a critical loophole in modern software quality assurance, especially those induced by language interactions (i.e., multilingual bugs ). Yet existing tool support for bug detection/localization remains largely limite…
The Linux kernel is highly-configurable, with a build system that takes a configuration file as input and automatically tailors the source code accordingly. Configurability, however, complicates testing, because different configuration options lead to the inclusion of different c…
We present FeatMaker , a novel technique that automatically generates state features to enhance the search strategy of symbolic execution. Search strategies, designed to address the well-known state-explosion problem, prioritize which program states to explore. These strategies t…
In large-scale online service systems, the occurrence of software changes is inevitable and frequent. Despite rigorous pre-deployment testing practices, the presence of defective software changes in the online environment cannot be completely eliminated. Consequently, there is a …
Due to the openness of the crowdsourced testing paradigm, crowdworkers submit massive spotty duplicate test reports, which hinders developers from effectively reviewing the reports and detecting bugs. Test report clustering is widely used to alleviate this problem and improve the…
Unit testing plays an essential role in detecting bugs in functionally-discrete program units ( e.g. , methods). Manually writing high-quality unit tests is time-consuming and laborious. Although the traditional techniques are able to generate tests with reasonable coverage, they…
The task of code generation aims to generate code solutions based on given programming problems. Recently, code large language models (code LLMs) have shed new light on this task, owing to their formidable code generation capabilities. While these models are powerful, they seldom…
We present LeJit , a template-based framework for testing Java just-in-time (JIT) compilers. Like recent template-based frameworks, LeJit executes a template—a program with holes to be filled—to generate concrete programs given as inputs to Java JIT compilers. LeJit automatically…
Static analyzers can reason about the properties and behaviors of programs and detect various issues without executing them. Hence, they should extract the necessary information to understand the analyzed program well. Annotation has been a widely used feature for different purpo…
Neural code summarization leverages deep learning models to automatically generate brief natural language summaries of code snippets. The development of Transformer models has led to extensive use of attention during model design. While existing work has primarily and almost excl…
Bug report reproduction is an important, but time-consuming task carried out during mobile app maintenance. To accelerate this task, current research has proposed automated reproduction techniques that rely on a guided dynamic exploration of the app to match bug report steps with…
Pythonic idioms are highly valued and widely used in the Python programming community. However, many Python users find it challenging to use Pythonic idioms. Adopting rule-based approach or LLM-only approach is not sufficient to overcome three persistent challenges of code idioma…