Related papers: Empirical Evaluation of AI-Assisted Software Packa…
We introduce API Pack, a massive multi-programming language dataset containing over one million instruction-API calls for improving the API call generation capabilities of large language models. Our evaluation highlights three key findings:…
Context: The rapid adoption of AI-assisted code generation tools, such as large language models (LLMs), is transforming software development practices. While these tools promise significant productivity gains, concerns regarding the…
Current software supply chains heavily rely on open-source packages hosted in public repositories. Given the popularity of ecosystems like npm and PyPI, malicious users started to spread malware by publishing open-source packages containing…
This paper presents a systematic review of Python packages with a focus on time series analysis. The objective is to provide (1) an overview of the different time series analysis tasks and preprocessing methods implemented, and (2) an…
Background: Recent innovations in generative artificial intelligence (AI) have transformed how programmers develop and maintain software. The advanced capabilities of generative AI tools in supporting development tasks have led to a rise in…
Large language models (LLMs) are now an integral part of software development workflows and are reshaping the whole process. Traditional technology stack selection has not caught up. Most of the existing selection methods focus solely on…
Open-source ecosystems such as NPM and PyPI are increasingly targeted by supply chain attacks, yet existing detection methods either depend on fragile handcrafted rules or data-driven features that fail to capture evolving attack semantics.…
The use of third-party packages is becoming increasingly popular and has led to the emergence of large software package ecosystems with a maze of inter-dependencies. Since the reliance on these ecosystems enables developers to reduce…
A plethora of scientific software packages are published in repositories, e.g., Zenodo and figshare. These software packages are crucial for the reproducibility of published research. As an additional route to scholarly knowledge graph…
Artificial Intelligence (AI) tools such as GitHub Copilot and ChatGPT are increasingly used in software engineering (SE) for tasks such as code, test, and documentation generation. However, engineers often face uncertainty about when to…
AI systems rest on software with low integrity mechanisms, leaving AI systems exposed across every stage from data acquisition to final inference. This paper makes the AI supply chain a first-class object of analysis, decomposing it across…
Purpose: Multicriteria decision analysis (MCDA) has become increasingly essential for decision-making in complex environments. In response to this need, the pyDecision library, implemented in Python and available at https://bit.ly/3tLFGtH,…
The increasing importance of Computational Science and Engineering has highlighted the need for high-quality scientific software. However, research software development is often hindered by limited funding, time, staffing, and technical…
In this research, we provide a comprehensive empirical summary of the Python Package Repository, PyPI, including both package metadata and source code covering 178,592 packages, 1,745,744 releases, 76,997 contributors, and 156,816,750…
As AI-powered code generation tools such as GitHub Copilot become popular, it is crucial to understand software developers' trust in AI tools -- a key factor for tool adoption and responsible usage. However, we know little about how…
Generative AI (genAI) tools promise productivity gains, yet miscalibrated trust and usage friction still hinder adoption. Moreover, genAI can be exclusionary, failing to adequately support diverse users. One such aspect of diversity is…
\textbf{Context:} Policy-as-Code (PaC) has become a foundational approach for embedding governance, compliance, and security requirements directly into software systems. While organizations increasingly adopt PaC tools, the software…
Estimating the effort of software systems is an essential topic in software engineering, carrying out an estimation process reliably and accurately for a software forms a vital part of the software development phases. Many researchers have…
Learning to use feature-rich software is a persistent challenge, but generative AI tools promise to lower this barrier by replacing complex navigation with natural language prompts. We investigated how people approach prompt-based tools for…
Machine learning applications, especially in the fields of me\-di\-cine and social sciences, are slowly being subjected to increasing scrutiny. Similarly to sample size planning performed in clinical and social studies, lawmakers and…