相关论文: ApacheJIT: A Large Dataset for Just-In-Time Defect…

The Just-In-Time (JIT) defect prediction model serves as a critical tool for ensuring the quality of software development and enhancing software performance. It assists development teams in promptly identifying and addressing potential…

Bug datasets are vital for enabling deep learning techniques to address software maintenance tasks related to bugs. However, existing bug datasets suffer from precise and scale limitations: they are either small-scale but precise with…

The increasing complexity of today's software requires the contribution of thousands of developers. This complex collaboration structure makes developers more likely to introduce defect-prone changes that lead to software faults.…

Defects4J is a large, peer-reviewed, structured dataset of real-world Java bugs. Each bug in Defects4J comes with a test suite and at least one failing test case that triggers the bug. In this paper, we report on an experiment to explore…

AI systems must adapt to evolving visual environments, especially in domains where object appearances change over time. We introduce Car Models in Time (CaMiT), a fine-grained dataset capturing the temporal evolution of car models, a…

Kubernetes is a tool that facilitates rapid deployment of software. Unfortunately, configuring Kubernetes is prone to errors. Configuration defects are not uncommon and can result in serious consequences. This paper reports an empirical…

Java applications include third-party dependencies as bytecode. To keep these applications secure, researchers have proposed tools to re-identify dependencies that contain known vulnerabilities. Yet, to allow such re-identification, one…

Bug fixing is generally a manually-intensive task. However, recent work has proposed the idea of automated program repair, which aims to repair (at least a subset of) bugs in different ways such as code mutation, etc. Following in the same…

Several software defect prediction techniques have been developed over the past decades. These techniques predict defects at the granularity of typical software assets, such as components and files. In this paper, we investigate…

Automated program repair (APR) aims to fix software bugs automatically without human debugging efforts and plays a crucial role in software development and maintenance. Despite promising, APR is still challenged by a long-standing…

Data of long-lived and high profile projects is valuable for research on successful software engineering in the wild. Having a dataset with different linked software repositories of such projects, enables deeper diving investigations. This…

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…

How can an end-user provide feedback if a deployed structured prediction model generates inconsistent output, ignoring the structural complexity of human language? This is an emerging topic with recent progress in synthetic or constrained…

Performance regressions in software systems can lead to significant financial losses and degraded user satisfaction, making their early detection and mitigation critical. Despite the importance of practices that capture performance…

Well-designed and publicly available datasets of bugs are an invaluable asset to advance research fields such as fault localization and program repair as they allow directly and fairly comparison between competing techniques and also the…

Just-in-time defect prediction (JIT-DP) aims to predict the likelihood of code changes resulting in software defects at an early stage. Although code change metrics and semantic features have enhanced prediction accuracy, prior research has…

Program repair is an important but difficult software engineering problem. One way to achieve acceptable performance is to focus on classes of simple bugs, such as bugs with single statement fixes, or that match a small set of bug…

High-quality and large-scale repositories of real bugs and their concise patches collected from real-world applications are critical for research in software engineering community. In such a repository, each real bug is explicitly…

Context: Software performance is a critical non-functional requirement, appearing in many fields such as mission critical applications, financial, and real time systems. In this work we focused on early detection of performance bugs; our…

Background. Defect prediction has been a highly active topic among researchers in the Empirical Software Engineering field. Previous literature has successfully achieved the most accurate prediction of an incoming fault and identified the…