相关论文: BugsInPy: A Database of Existing Bugs in Python Pr…

Large Language Models (LLMs) have demonstrated strong natural language processing and code synthesis capabilities, which has led to their rapid adoption in software engineering applications. However, details about LLM training data are…

Python has emerged as one of the most popular programming languages, extensively utilized in domains such as machine learning, data analysis, and web applications. Python's dynamic nature and extensive usage make it an attractive candidate…

Deep learning has gained substantial popularity in recent years. Developers mainly rely on libraries and tools to add deep learning capabilities to their software. What kinds of bugs are frequently found in such software? What are the root…

Large language models (LLMs) have demonstrated strong performance on a wide range of software engineering tasks, including code generation and analysis. However, most prior work relies on cloud-based models or specialized hardware, limiting…

Understanding how software defects manifest and evolve in production environments is critical for improving reliability. While previous research has largely focused on pre-release defects, the nature of residual faults, i.e., those escaping…

With the growing interest on Large Language Models (LLMs) for fault localization and program repair, ensuring the integrity and generalizability of the LLM-based methods becomes paramount. The code in existing widely-adopted benchmarks for…

Software is used in critical applications in our day-to-day life and it is important to ensure its correctness. One popular approach to assess correctness is to evaluate software on tests. If a test fails, it indicates a fault in the…

TypeScript has rapidly become a popular language for modern web development, yet its effect on software faults remains poorly understood. This paper presents the first large-scale empirical study of bugs in real-world TypeScript projects.…

In this paper, we first collect and track a large number of fixed and unfixed violations across revisions of software. The empirical analyses reveal that there are discrepancies in the distributions of violations that are detected and those…

Test-based automated program repair has been a prolific field of research in software engineering in the last decade. Many approaches have indeed been proposed, which leverage test suites as a weak, but affordable, approximation to program…

Developers are increasingly using services such as Dependabot to automate dependency updates. However, recent research has shown that developers perceive such services as unreliable, as they heavily rely on test coverage to detect conflicts…

Most Software Engineering (SE) human-based controlled experiments rely on students as participants, raising concerns about their external validity. Specifically, the realism of results obtained from students and their applicability to the…

Code large language models (LLMs) have made significant progress in code debugging by directly generating the correct code based on the buggy code snippet. Programming benchmarks, typically consisting of buggy code snippet and their…

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…

Flaky tests are tests that can non-deterministically pass or fail, even in the absence of code changes.Despite being a source of false alarms, flaky tests often remain in test suites once they are detected, as they also may be relied upon…

Jupyter notebooks are widely used for machine learning (ML) prototyping. Yet, few debugging tools are designed for ML code in notebooks, partly, due to the lack of benchmarks. We introduce JunoBench, the first benchmark dataset of…

Bug-fix benchmarks are fundamental in advancing various sub-fields of software engineering such as automatic program repair (APR) and fault localization (FL). A good benchmark must include recent examples that accurately reflect…

Third-party dependency updates can cause a build to fail if the new dependency version introduces a change that is incompatible with the usage: this is called a breaking dependency update. Research on breaking dependency updates is active,…

Automated Program Repair (APR) plays a critical role in enhancing the quality and reliability of software systems. While substantial progress has been made in Java-based APR, largely facilitated by benchmarks like Defects4J, there remains a…

The joint task of bug localization and program repair is an integral part of the software development process. In this work we present DeepDebug, an approach to automated debugging using large, pretrained transformers. We begin by training…