Related papers: CIDR: A Large-Scale Industrial Source Code Dataset…
As software systems grow increasingly complex, ensuring security during development poses significant challenges. Traditional manual code audits are often expensive, time-intensive, and ill-suited for fast-paced workflows, while automated…
Automation of code reviews using AI models has garnered substantial attention in the software engineering community as a strategy to reduce the cost and effort associated with traditional peer review processes. These models are typically…
Continuous integration and delivery (CI/CD) pipelines are critical for sustaining the evolution of large software systems. In regulated industries with legacy technologies, however, pipelines themselves can become a source of technical…
Code data in large language model (LLM) pretraining is recognized crucial not only for code-related tasks but also for enhancing general intelligence of LLMs. Current open-source LLMs often heavily rely on human effort to produce their code…
As cloud environments become widespread, cybersecurity has emerged as a top priority across areas such as networks, communication, data privacy, response times, and availability. Various sectors, including industries, healthcare, and…
With the increasing adoption of Continuous Integration and Continuous Deployment pipelines, securing software supply chains has become a critical challenge for modern DevOps teams. This study addresses these challenges by applying a…
The race to train language models on vast, diverse, and inconsistently documented datasets has raised pressing concerns about the legal and ethical risks for practitioners. To remedy these practices threatening data transparency and…
Recent research has demonstrated that artificial intelligence (AI) can assist electronic design automation (EDA) in improving both the quality and efficiency of chip design. But current AI for EDA (AI-EDA) infrastructures remain fragmented,…
Software Engineering 3.0 marks a paradigm shift in software development, in which AI coding agents are no longer just assistive tools but active contributors. While prior empirical studies have examined productivity gains and acceptance…
Hydra is a full-scale industrial CFD application used for the design of turbomachinery at Rolls Royce plc. It consists of over 300 parallel loops with a code base exceeding 50K lines and is capable of performing complex simulations over…
Performance bugs challenge software development, degrading performance and wasting computational resources. Software developers invest substantial effort in addressing these issues. Curating these performance bugs can offer valuable…
The intersection of Artificial Intelligence and Digital Humanities enables researchers to explore cultural heritage collections with greater depth and scale. In this paper, we present EUFCC-CIR, a dataset designed for Composed Image…
We describe the CZ Software Mentions dataset, a new dataset of software mentions in biomedical papers. Plain-text software mentions are extracted with a trained SciBERT model from several sources: the NIH PubMed Central collection and from…
Choral singing, a widely practiced form of ensemble singing, lacks comprehensive datasets in the realm of Music Information Retrieval (MIR) research, due to challenges arising from the requirement to curate multitrack recordings. To address…
Spurred by recent advances in Large Language Models (LLMs), virtual assistants are poised to take a leap forward in terms of their dialogue capabilities. Yet a major bottleneck to achieving genuinely transformative task-oriented dialogue…
Reproducibility and replicability are critical pillars of empirical research, particularly in machine learning, where they depend not only on the availability of models, but also on the datasets used to train and evaluate those models. In…
This paper introduces SBAN (Source code, Binary, Assembly, and Natural Language Description), a large-scale, multi-dimensional dataset designed to advance the pre-training and evaluation of large language models (LLMs) for software code…
Security patches in open-source software, providing security fixes to identified vulnerabilities, are crucial in protecting against cyberattacks. Despite the National Vulnerability Database (NVD) publishes identified vulnerabilities, a vast…
We constructed a newly large-scale and comprehensive C/C++ vulnerability dataset named MegaVul by crawling the Common Vulnerabilities and Exposures (CVE) database and CVE-related open-source projects. Specifically, we collected all…
Composed image retrieval (CIR) enables users to search images using a reference image combined with textual modifications. Recent advances in vision-language models have improved CIR, but dataset limitations remain a barrier. Existing…